Dynamic contrast-enhanced MRI vs. mammography for preoperative tumor sizing in primary breast cancer: correlation with histopathology

Authors

Abstract

AimAccurate preoperative tumor sizing is crucial for surgical planning in breast cancer. We aimed to compare tumor size on mammography and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with pathologic size and evaluate inter-observer agreement.

MethodsIn this single-center retrospective cohort study, 65 women (mean age 52.01 ± 9.97 years) who underwent preoperative mammography and breast MRI without neoadjuvant therapy, followed by total or modified radical mastectomy (January 01, 2014–October 31, 2020), were included. Two radiologists independently measured the maximal lesion diameter on mammography and DCE-MRI. A single pathologist measured the maximal invasive or in situ tumor diameter in the surgical specimens. Spearman’s correlation and Bland–Altman analyses were performed.

ResultsThe mean maximal diameters (mm) were as follows: pathology, 34.27 (SD 20.42); MRI, 32.72 and 33.04 (readers 1/2), and mammography, 25.69 and 26.12. MRI–pathology correlations were very good (r = 0.891 and 0.888; both P < 0.001), exceeding mammography–pathology correlations (r = 0.727 and 0.724; both P < 0.001). Compared with pathology, MRI showed a small positive bias (+1.39 mm; 95% LoA −14.59 to 17.38) versus a larger bias and wider dispersion for mammography (+8.36 mm; 95% LoA −24.66 to 41.40 mm).

ConclusionsDCE-MRI provides more accurate and reproducible preoperative tumor size estimation than mammography, with a stronger correlation with pathology and tighter limits of agreement. The selective use of MRI is justified when precise sizing influences surgical management.

Keywords

Introduction

Given that breast cancer remains the most frequently diagnosed cancer and a leading cause of cancer-related mortality in women worldwide, early and accurate assessment is crucial for clinical decision-making and prognosis.¹ The maximal diameter determines eligibility for breast-conserving surgery, extent of resection, and nodal assessment, and contributes to pathologic staging and prognosis.² Discrepancies between radiologic and histopathologic measurements may result in incomplete tumor excision, reoperation, or overtreatment.³
Mammography remains the workhorse for detection and diagnostic triage.² It has high specificity (>90%) but limited sensitivity (~70%), with higher false positives and negatives in women with dense breasts, who comprise nearly half of the screening population.⁴
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides high sensitivity, multiplanar coverage, and contrast-based delineation that sharpens margins and reveals satellite foci or non-mass enhancement.⁵ However, concerns remain about variable specificity and potential size overestimation, particularly in extensive ductal carcinoma in situ (DCIS), and performance depends on acquisition parameters and reader expertise.⁶
Prior reports of imaging–pathology concordance are heterogeneous, reflecting differences in case mix, histologic subtypes, and analytic approach.^7,8 In some cohorts, MRI8 correlates most closely with pathology, while in others, mammography^7,9 or ultrasound¹⁰ does. Uncertainty in preoperative sizing translates into margin risk, re-excisions, and potential overtreatment.³
Therefore, we aimed to identify the imaging modality that best approximates histopathologic tumor size by comparing mammography and DCE-MRI using correlation and agreement metrics, with inter-observer reproducibility as a secondary outcome.

Materials and Methods

Study Design and Population
We performed a retrospective observational study of consecutive women who underwent preoperative mammography and DCE-MRI, followed by total or modified radical mastectomy between January 1, 2014, and October 31, 2020. The inclusion criteria were available diagnostic mammography and breast MRI of adequate quality, and available pathology reports. The exclusion criteria comprised prior neoadjuvant therapy, inadequate imaging, missing tumor size in the pathology report, and pediatric age. The final cohort included 65 women (mean age 52.01 ± 9.97; range 31–75 years) (Figure 1).
Imaging AcquisitionStandard two-projection mammography was performed (Selenia Dimensions, Hologic, GmbH,Belgium, Germany).
MRI (3T; Skyra; Siemens Healthcare, Germany) examinations included axial pre-contrast and dynamic post-contrast three-dimensional (3D) T1-weighted acquisitions. Gadolinium (Dotarem) was administered at 0.2 mmol/kg via a power injector. Six post-contrast series were obtained at 60-s intervals. Representative parameters were as follows: 3D T1-weighted fast low-angle shot (FLASH), TR 4.51 ms, TE 1.61 ms, flip angle 10°, matrix 448 × 300, slice thickness 1.10 mm with 0.2 mm interslice gap. Subtraction images were generated for the lesion analysis.
Image AnalysisAll measurements were performed by two board-certified breast radiologists (18 and 5 years of experience) on the same calibrated Picture Archiving and Communication System (PACS) workstation using a standardized hanging protocol and fixed window/level presets. The readers were blinded to each other’s measurements and pathology reports. For MRI, the breast imaging reporting and data system (BI-RADS) category and enhancement kinetics (types 1, 2, and 3) were recorded.¹¹ Mammographic density was assigned according to the ACR categories A–D.11 Tumor size on MRI was defined as the in-plane maximal diameter on subtracted early post-contrast images, measured in the plane of greatest conspicuity, and multiplanar reconstructions were not used for sizing.
For mammography, the size was the longest measurable dimension on diagnostic views; in pure DCIS, the maximal calcification span was recorded.
PathologyA single dedicated pathologist measured the maximum tumor diameter in the surgical specimens. The pathology reference was the greatest invasive (or in situ, when applicable) diameter on the surgical specimen, according to the institutional protocol.
OutcomesThe primary outcome was the correlation between the imaging-based maximal diameter (per reader and modality) and histologic diameter (Spearman’s r). Secondary outcomes included descriptive diameter distributions, inter-observer agreement, and agreement between imaging and histology, assessed via Bland–Altman plots using the average of the two readers for each modality.
Ethical ApprovalThis study was approved by the Ethics Committee of the Yıldırım Bayezit University Hospital (Date: 2020-12-16, No: 26379996/127).
Statistical AnalysisContinuous variables are summarized as mean (SD) or median (IQR), as appropriate. Spearman correlation coefficients (r) were interpreted as none/weak (<0.25), weak–moderate (0.25–0.50), good (0.50–0.75), and very good (≥0.75). Bland–Altman analysis was used to determine the mean differences (bias) and 95% limits of agreement (LoA). Analyses were performed using SPSS v22 and MedCalc. Two-sided P-values < 0.05 were considered statistically significant.
Reporting GuidelinesThis study is reported in accordance with the STROBE guidelines.

Results

The 65 patients had a mean age of 52.01 ± 9.97 years. ACR breast density distribution on mammography was: A: 13.8% (n = 9), B: 32.3% (n = 21), C: 36.9% (n = 24), D: 16.9% (n = 11). On MRI, the BI-RADS categories were 4 in 32.3% (n = 21), 5 in 56.9% (n = 37), and 6 in 10.8% (n = 7). Enhancement kinetics were Type 1 in 4.6% (n = 3), Type 2 in 52.3% (n = 34), and Type 3 in 43.1% (n = 28) of patients (Supplementary Table 1).
The final diagnoses were invasive ductal carcinoma (IDC) in 61.5% (n = 40), invasive lobular carcinoma in 4.6% (n = 3), pure DCIS in 7.7% (n = 5), lobular carcinoma in situ (LCIS) in 1.5% (n = 1), and mixed in-situ lesions in 18.5% (n = 12).
The mean maximal diameters (mm) were as follows: pathology, 34.27 (SD 20.42); MRI, 32.72 (reader 1) and 33.04 (reader 2); and mammography, 25.69 (reader 1) and 26.12 (reader 2) (Table 1).
MRI-to-histology correlations were very good (r = 0.891 and r = 0.888, both P < 0.001). Mammography-to-histology correlations were good: r = 0.727 and r = 0.724 (both P < 0.001).
In MRI measurements, we found a small but statistically non-zero inter-reader bias (Reader 1 − Reader 2:0.3 mm, 95% CI 0.016–0.63), with Bland–Altman limits of agreement −2.10 to 2.75 mm (lower LoA 95% CI −2.63 to −1.57; upper LoA 95% CI 2.22 to 3.27), indicating high reproducibility with clinically negligible dispersion (Figure 2).
In mammography measurements, the inter-reader bias was 0.43 mm (95% CI 0.09–0.76), and the limits of agreement were −2.22 to 3.09 mm (lower LoA 95% CI −2.80 to −1.65; upper LoA 95% CI 2.51 to 3.66), likewise reflecting tight agreement despite a statistically detectable but small bias (Supplementary Figure 1 shows the Bland-Altman Graphic of these results).

The mean difference (MRI − pathology) was +1.39 mm (95% CI: −0.62 to 3.41), indicating a small, statistically detectable, positive bias. The Bland–Altman limits of agreement were −14.59 to 17.38 mm (lower LoA 95% CI −18.07 to −11.12; upper LoA 95% CI 13.91 to 20.85) (Supplementary Figure 2 shows the Bland-Altman Graphic of these results).
The mean difference (mammography − pathology) was +8.36 mm (95% CI 4.19–12.54), indicating a systematic overestimation relative to histology. The Bland–Altman limits of agreement were −24.66 to 41.40 mm (lower LoA 95% CI −31.84 to −17.49; upper LoA 95% CI 34.23–48.57) (Supplementary Figure 3 shows the Bland Altman Graphic of these results).

Discussion

In this mastectomy-only cohort with a realistic density profile (ACR C/D, 53.8%) and invasive-predominant histology (IDC 61.5%), tumor size measurements in DCE-MRI demonstrated superior fidelity to pathology compared with those in mammography.
Correlations with pathology were very good for MRI (r≈0.89 for both readers) and only good for mammography (r≈0.72). More importantly, for surgical planning, agreement analyses favored MRI: the mean MRI–pathology bias was small (+1.39 mm; 95% CI −0.62 to 3.41) with 95% limits of agreement (LoA) −14.59 to 17.38 mm, whereas mammography showed a larger systematic overestimation (+8.36 mm; 95% CI 4.19–12.54) and much wider LoA (−24.66 to 41.40 mm). In practical terms, MRI’s error band of (~32 mm total span) was roughly half that of mammography (~66 mm), increasing the chance that a preoperative estimate falls within a clinically acceptable window when millimeters decide margins.
The direction and magnitude of mammographic bias in our series—overestimation rather than the commonly reported underestimation—likely reflect cohort and measurement context. First, the density profile (ACR C/D (~54%)) and presence of in-situ components (pure/mixed ~26%) may enlarge apparent mammographic extent (e.g., calcification span, architectural distortion) beyond the invasive diameter on final pathology. This is also technically plausible: lesion edges can blur in dense parenchyma, architectural distortion, and non-calcified DCIS are harder to bound, and two-dimensional projection compresses three-dimensional reality.^12,13 This supports MRI use when breast-conserving surgery (BCS) margins are expected to be tight, breasts are dense (ACR C/D), imaging is discordant, or disease appears irregular/multifocal.
According to a previous study, MRI has the best imaging–pathology concordance, surpassing mammography and ultrasonography in absolute size agreement and correlation (r = 0.80 vs. 0.57 and 0.26, respectively).8 In another 261-patient IDC/invasive lobular carcinoma (ILC) cohort, MRI and ultrasound correlated similarly and strongly with pathological size (r = 0.76 vs. 0.71; P>0.05, Zou’s method), and both outperformed mammography and clinical examination (P < 0.05). Agreement testing (McNemar) also favored MRI/US, suggesting that either modality provides reliable preoperative size estimates, with no clear advantage of MRI over ultrasound.¹⁴
Another study reported similar ultrasound and MRI correlation with pathologic size. Among 76 patients (84 lesions), MRI showed the highest concordance with pathology (82.1%), exceeding ultrasound (76.2%) and mammography (64.3%). Discordance direction varied; ultrasound/mammography underestimated (70%), whereas MRI overestimated (80%). Importantly, on MRI, non-mass enhancement (NME) alone or with a mass significantly increased discordance risk (OR, 17.2; P = 0.030 and OR, 51.0; P = 0.001, respectively). In summary, they stated that MRI is generally more accurate, but measurements should be interpreted cautiously when NME is present.¹⁵
In another retrospective cohort (n = 87), MRI–pathology size concordance was 69%, with MRI overestimation in 24% and underestimation in 7% of cases.¹⁶ In multivariable analysis, associated DCIS was the sole predictor of MRI overestimation (OR 9.0; 95% CI 1.13–71.87; P = 0.038).16 These data support caution that MRI is generally accurate but prone to positive bias when DCIS coexists.16 Similarly, in a 115-lesion cohort, MRI performance depended on size derivation: in-plane maximal diameter best matched excision-relevant pathology (86% concordance; over/underestimation 9%/5%; bias ~0.2 mm), whereas MRI-MPR vs. Path-TNM showed larger systematic error (+7.1 mm). Non-mass enhancement was the only independent predictor of discordance (P<0.001), with overestimation far more frequent for NME (41%) than masses (7%).¹⁷
In contrast, non-selective preoperative MRI added to mammography and ultrasound shows weak size concordance with pathology, especially for larger tumors, with both under- and overestimation (>10 mm in 4.6% and 7.5%) and higher mastectomy rates in misestimated cases (56–65% vs. 43%).¹⁸ IDC with extensive DCIS is best measured by MRI, whereas ultrasound underestimates size.7 MRI may also better estimate DCIS extent than conventional imaging.¹⁹ However, MRI improves detection of multifocal disease (78% vs. 37% by MG/US; total 84%) and contralateral disease (all cases), supporting selective rather than routine use.¹⁸
Mammography measurements are also close to pathological dimensions. In a community-based setting, preoperative size estimates from MG, US, and MRI in 161 women (169 lesions) closely matched pathology. Correlations were similar for MG and MRI (r = 0.76 and 0.75) and lower for US (r = 0.67); mean sizes were 1.90 cm (MG), 1.87 cm (US), and 2.40 cm (MRI) versus 2.19 cm on pathology. Overall, all modalities performed well, with MRI offering incremental value for selected patients beyond MG/US.²⁰
In a prior retrospective series, IDC size was measurable across all three main modalities; MRI and mammography were more accurate, whereas sonography showed a statistically significant size underestimation, particularly for larger tumors.⁷ They showed that DCIS-only lesions were most accurately measured by mammography, with both mammography and MRI exhibiting no significant deviation from the histologic size.⁷ Likewise, for DCIS, another cohort (n = 104) reported stronger size concordance with pathology on mammography than on ultrasound (overall r = 0.786 vs. 0.651).²¹ The advantage for mammography persisted across density strata—fatty/scattered (r = 0.790 vs 0.678) and heterogeneously/extremely dense (r = 0.770 vs 0.548)—and in both microcalcification-positive (r = 0.772 vs 0.570) and -negative groups (r = 0.806 vs 0.783).21 Conversely, in another study with 56 DCIS patients, size measurements—when lesions were visible—aligned well with pathology, with the highest reliability on US (κ = 0.851), followed by mammography (κ = 0.815) and MRI (κ = 0.738).22 The accuracy improved when lesions appeared as masses on US (P = 0.003) or MRI (P<0.001), and when minimal or mild BPE was present on MRI (P = 0.016). On mammography, ER-positive and luminal A tumors were more accurately sized than triple-negative tumors.²²
Across molecular subtypes, multicenter data show MRI yields the strongest pathology concordance in invasive/mixed tumors and remains relatively robust in DCIS (MRI r≈0.77–0.83 vs. US r≈0.66–0.77; MMG lower), whereas a separate cohort reported systematic underestimation in luminal A across all three modalities, most pronounced with US and MMG (MRI P = 0.020; MMG P = 0.030; US P<0.001), which worsened with increasing size.^23,24
In ILC, a cohort of 111 BCS patients showed MRI estimated size more closely than mammography or ultrasound (r = 0.58 vs. 0.17 and 0.37; mean 2.51 cm vs. 2.64 cm pathology), with fewer ≥1 cm underestimations (13.3% vs. 27.1% MMG and 50% US).25 However, imaging–pathology correlations were modest overall, and preoperative MRI did not reduce re-excision rates (30.3% vs. 40.0%; P = 0.31), indicating that improved MRI sizing may not translate into fewer reoperations for ILC.²⁵
A single-center retrospective study (n = 56 invasive cancers) found that ultrasound best predicted pathologic size (r = 0.68), outperforming clinical examination (r = 0.62), mammography (r = 0.57), and MRI (r = 0.51).¹⁰ On average, clinical examination, US, and mammography underestimated tumor size (all P<0.05), whereas MRI overestimated it (22.5 vs. 16.1 mm; P>0.05). These data support US as the most size-accurate modality in that cohort and highlight MRI’s overestimation tendency, which is a useful context when interpreting modality-specific biases in our series.¹⁰

Limitations

First, this single-center retrospective cohort (n = 65) may limit subgroup power (e.g., DCIS, ILC, mass vs non-mass) and overfit local practice patterns. Second, only two modalities were evaluated, and not all literature comparators were assessed, limiting full modality triage. Thus, phenotype-level failure modes—especially non-mass enhancement and coexisting DCIS, which bias MRI high—were underpowered for definitive stratified estimates and should be interpreted cautiously. Finally, sizing error was not linked to clinical (margin positivity, re-excision, mastectomy conversion, excised-volume ratio, delays to adjuvant therapy) or health-system outcomes (additional biopsies, costs), so management impact remains inferential.
Future work should include multicenter prospective cohorts, head-to-head comparisons with phenotype-stratified analyses (DCIS/NME, ILC, density bins), inter-reader ICCs, explicit clinical endpoints, and decision-curve analyses to translate sizing fidelity into surgical benefit.

Conclusion

DCE-MRI estimates preoperative tumor size closer to histopathology than mammography, which matters when millimeters determine breast-conserving margins. Given MRI’s overestimation risk in non-mass enhancement/DCIS and the underestimation tendency of US/MG, use should be selective and phenotype-driven. Standardizing MRI to the in-plane maximal diameter and reporting an uncertainty band (e.g., ± 5–10 mm in high-risk contexts) may improve surgical planning and reduce unplanned re-excisions.

Declarations

Abbreviations

ACR: American College of Radiology
BI-RADS: Breast Imaging Reporting and Data System
CI: Confidence interval
DCIS: Ductal carcinoma in situ
DCE-MRI: Dynamic contrast-enhanced magnetic resonance imaging
FLASH: Fast low-angle shot
IDC: Invasive ductal carcinoma
ILC: Invasive lobular carcinoma
IQR: Interquartile range
LCIS: Lobular carcinoma in situ
LoA: Limits of agreement
MG: Mammography
MRI: Magnetic resonance imaging
NME: Non-mass enhancement
OR: Odds ratio
PACS: Picture Archiving and Communication System
SD: Standard deviation
SPSS: Statistical Package for the Social Sciences
STROBE: Strengthening the Reporting of Observational Studies in Epidemiology
TE: Echo time
TR: Repetition time
US: Ultrasonography

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About This Article

Received:

February 14, 2026

Accepted:

April 24, 2026

Published Online:

April 29, 2026