Evidence map›Paper›PMID 40522576›Full record

ArticleAnnals of surgical oncology2025

Sizing It Up: Concordance between Breast Imaging and Pathologically Determined Tumor Measurement.

Abigail E Daly, Kyle J Anderman, Logan R Holt, Tyler P Shern, Manisha Bahl, Michelle A Gadd, Michelle C Specht, Francys C Verdial, Rebecca Kwait, Barbara L Smith and 1 more

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Article in Annals of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

11 authors.

Abigail E DalyBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Kyle J AndermanBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Logan R HoltBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Tyler P ShernBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Manisha BahlDepartment of Radiology, Massachusetts General Hospital, Boston, MA, USA.
Michelle A GaddBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Michelle C SpechtBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Francys C VerdialBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Rebecca KwaitBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Barbara L SmithBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA.
Tolga OzmenBreast Section, Division of Gastrointestinal and Oncologic Surgery, Massachusetts General Hospital, MGH Center for Breast Cancer, Boston, MA, USA. tozmen@mgh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate preoperative imaging of breast tumor size is essential, as small measurement differences can influence the treatment strategy. This study evaluates the accuracy of tumor size estimation by mammography, ultrasound, and magnetic resonance imaging (MRI) compared with pathology and examines factors influencing imaging performance. PATIENTS AND

methodsWe retrospectively analyzed patients with breast cancer treated from 2019 to 2024. Measurements were considered concordant if they fell within ±20% of the pathological size. Statistical analyses performed include paired t-tests, chi-squared tests, Lin's concordance correlation coefficient (CCC), and logistic regression. Python-based framework was used to identify the most accurate weighted formula.

resultsWe included 460 patients with a median age of 57 (26-90) years. MRI had the highest concordance (62%), outperforming mammography (57%) and ultrasound (53%) (p = 0.004). Our alternative weighted average formula (0.66 × MRI size + 0.35 × US size) yielded the highest concordance rate (65.2%, CCC = 0.785). Average tumor size on pathology was 17.31 mm. MRI slightly overestimated the size (18.38 mm, p = 0.482), while mammography (14.8 mm, p = 0.06) and ultrasound (14.31 mm, p = 0.019) underestimated. MRI demonstrated the highest accuracy in T-stage classification (89%). Concordance was highest for masses without non-mass enhancement (NME) (CCC = 0.834) and declined with NME (CCC = 0.635). MRI accuracy improved in tumors > 15 mm (OR 2.47) and high-grade tumors (OR 1.75) but declined in extremely dense breasts (OR 0.42) and lobular histology (OR 0.46).

conclusionsMRI demonstrated the highest concordance with tumor size and T stage. Its accuracy improved in larger and high-grade tumors but decreased with dense breasts, NME, and lobular histology. A combined imaging approach using MRI and ultrasound may enhance preoperative size estimation.

Indexed as

Breast cancerImaging accuracyMammographyMRITumor size estimationUltrasound

Identifiers

PMID40522576

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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.