Introduction

Breast cancer is a major cause of cancer-related deaths in women. Despite advances in treatment and diagnostic techniques, breast cancer accounted for approximately 680,000 deaths in 2020 worldwide [1]. Metastatic breast cancer is responsible for most cancer-related deaths and spreads to other body sites through the bloodstream and lymphatics. Accurate axillary nodal staging is clinically important because it reflects disease progression at diagnosis and helps determine the optimal treatment intensity. Magnetic resonance imaging (MRI) and ultrasonography (US) are frequently used for nodal evaluation in clinical settings; however, MRI has better diagnostic accuracy than US because US is highly operator-dependent [2].

Invasive lobular carcinoma (ILC) is the most common special subtype of breast cancer, accounting for 10–15% of all breast cancer cases [3]. ILC is characterized by E-cadherin loss, which is crucial in cell–cell adhesion, and typically shows small and non-cohesive epithelial cells dispersed individually. Its clinical presentation differs from that of invasive ductal carcinoma (IDC); Chung et al. reported a different morphology of axillary lymph node (ALN) metastasis for ILC from that of IDC on US [4]. ILC has subtle imaging findings both on mammography and US because ILC frequently appears with a mass density that is less than or equal to that of normal fibroglandular breast tissue on a mammograph, and sometimes shows only a slight architectural distortion on US. Therefore, MRI is recommended to evaluate tumor extent [5]. We hypothesized that a distinct MRI interpretation may be necessary to predict ILC nodal staging; however, the clinical evidence is limited.

We aimed to identify a specific imaging feature of MRI that is highly associated with ALN metastasis of ILC. Based on the previously reported findings [6,7,8], in this study, we investigated the imaging features correlated with lymph node metastasis for the nodal ILC. We then constructed a logistic regression model and evaluated its diagnostic accuracy using receiver operating characteristic (ROC) analysis.

Material and methods

Patients

From a hospital breast cancer registry in Japan, we retrospectively identified 169 Asian women diagnosed with ILC via core needle biopsy between April 2011 and June 2022. The exclusion criteria included the absence of MRI data (n = 32), neoadjuvant chemotherapy history (n = 13), neoadjuvant endocrine therapy history (n = 3), and coronavirus disease vaccination 6 months prior (n = 1). Overall, 120 women were eligible and randomized to the derivation cohort (Fig. 1). Tumor and nodal stages were allocated according to the Tumor–Node–Metastasis (TNM) staging system proposed by the American Joint Committee on Cancer, 8th edition [9]. The relevant ethics committee approved the study protocol (registration number: 1552). Since the study was retrospective and anonymous, the requirement for informed consent was waived.

Fig. 1
figure 1

Study design. a Patient enrolment flowchart. The chart shows the screening of 169 patients who underwent breast surgeries for primary invasive lobular carcinoma in our hospital between April 2011 and June 2022. b The steps of data analysis. ALN axillary lymph node, ET endocrine therapy, ILC invasive lobular carcinoma, MRI magnetic resonance imaging, NAC neoadjuvant chemotherapy

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Imaging protocol

We used a 3.0-Tesla (T) MRI to assess the nodal staging and tumor extension of primary breast cancer with patients in the prone position, with their arms laid down. At our institution, dynamic contrast-enhanced MRI was performed using a 3.0-Tesla (T) MRI scanner (Ingenia, Philips Healthcare, Best, The Netherlands) with seven-channel breast coils. T1-weighted imaging (TR/TE, 640/10 ms; phase encoding direction, right-to-left; flip angle, 90º; field of view, 320 × 320 mm, thickness, 3 mm; matrix, 304 × 384) and T2-weighted imaging with fat suppression (TR/TE, 10,700/80 ms; phase encoding direction, right-to-left; flip angle, 80°; field of view, 320 × 320 mm, thickness, 3 mm; matrix, 288 × 288) were obtained as one pre-contrast imaging. After intravenous administration of gadoteridol (Prohance, Bracco, Milan, Italy) using a single dose of 0.1 mmol/kg body weight at a flow rate of 3 ml/s, dynamic contrast-enhanced, fat-suppressed, gradient echo, and T1-weighted axial imaging (TR/TE, 3.8/1.95 ms; phase encoding direction, right-to-left; flip angle, 12°; field of view, 320 × 320 mm; thickness, 2 mm; matrix, 352 × 384) was performed. Sequential acquisitions of the four post-contrast images were obtained at 60 s, 120 s, 180 s, and 360 s.

Imaging analysis

The images or standardized reports of imaging findings of ALNs were collected from the electronic medical records. Morphological evaluation was performed according to criteria from previous reports [10]. Breast and axillary MR images were retrospectively reviewed; the readers were blinded to the clinical information regarding ALN analysis during radiogram interpretation. Two readers (S.K. and H.K. [breast surgeons with 5 and > 20 years of experience, respectively]) separately performed image analysis. When disagreements occurred, the third reader, an experienced radiologist (T.M.) with > 20 years of experience in MRI interpretation, was consulted. In the interpretation session, all detectable ALNs at least 3 mm in long-axis diameter were measured on both sides. Four images were obtained at 60 s, 120 s, 180 s, and 360 s in the post-contrast phase of the T1-weighted axial imaging when the primary lesion and ALNs were most clearly visualized, and the following were recorded: maximum long-axis diameter (LAD), maximum cortical thickness, the presence of focal cortical thickening (FCT) (Fig. 2), and the presence of loss of hilum (LOH). The maximum cortical thickness was measured perpendicular to the long axis of the ALNs in a transverse direction. FCT was defined as non-uniform cortical thickening showing single or multiple bulges protruding from the lymph node cortex. When LOH was suspected, the short-axis diameter was substituted for the cortical thickness. LOH was judged as positive only when the short-axis diameter was ≥ 4 mm on MRI [11]. When LOH or FCT was observed, the lymph node data presenting such features were selected.

Fig. 2
figure 2

Representative images of a 60-year-old female patient with ALN metastasis of invasive lobular carcinoma (pT1cN1aM0, pStage IIA; Luminal B-like type). a Transverse contrast-enhanced T1-weighted magnetic resonance image showing an enlarged axillary lymph node in level I, presenting FCT (red arrow). b Panoramic-view metastatic ALN image showing eccentric FCT of the nodular metastatic foci. c Solid components consisting of discohesive tumor cells with round nuclei (grade 2 nuclear score) within the metastatic ALN (hematoxylin and eosin staining; [b] × 20, [c] × 200). ALN axillary lymph node, FCT focal cortical thickening

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Axillary surgery

Sentinel lymph node biopsy was performed using the dual method with phytate sodium hydrate, technetium-phytic acid, and indigo carmine. The sentinel lymph nodes were frozen, sectioned at a thickness of 2 mm, and sent to expert pathologists to determine whether they contained cancer cells. Based on the quick examination of sentinel lymph node results, we performed or omitted ALN sampling or ALN dissection to level I/II based on the case corresponding to the ACOSOG Z0011 trial [12].

Pathological evaluation

Tissue specimens were obtained through preoperative core needle or vacuum-assisted biopsies. The detailed pathological evaluations are described in the Supplementary Material (online).

Statistical analysis

Numeric data are expressed as mean ± standard deviation (SD). Continuous variables were compared between the two groups using the Student’s t-test. The optimal cut-off values for Ki-67, tumor size, LAD, cortical thickness, and FCT were determined using ROC analysis based on the Youden index. We first identified significant factors (p < 0.05) associated with ALN metastasis in a univariate analysis using Fisher’s exact test. Then, the diagnostic accuracy was assessed using the AUC values of the logistic regression models. The percentage FCT agreement was evaluated using kappa statistics. Statistical analyses were performed using R: a language and environment for statistical computing version, 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria). A p-value lower than 0.05 was accepted as the significance level for all analyses.

Results

Of the 120 female patients with ILC (mean ± SD age, 57.2 ± 11.2 years) in the derivation cohort, 35 (29%) had ALN metastases. Primary ILC exhibited a T category of T1 in 56% (67/120), T2 in 33% (40/120), and T3 in 11% (13/120), and an N category of N1mi in 3% (3/120), N1a in 18% (21/120), N2a in 6% (7/120), and N3a in 3% (4/120). The pathological TNM stage was IA in 43% (52/120), IB in 1% (1/120), IIA in 33% (40/120), IIB in 10% (12/120), IIIA in 9% (11/120), and IIIC in 3% (4/120) of the patients.

Table 1 summarizes the patient characteristics and statistical comparisons between the two groups with or without ALN metastasis in the derivation cohort. Pathological tumor size and histological grade were significantly greater in patients with ALN metastasis (p < 0.05). The cut-off value of cortical thickness change defining ‘FCT-positive’ was identified as 2 mm at the level with the highest area under the curve (AUC) value by ROC analysis as in Fig. 3. In the derivation cohort, FCT and LOH were present in 41 (34%) and 23 (19%) patients on MRI, respectively. Of the 35 patients who had ALN metastasis, 32 (91%) and 6 (17%) patients had FCT and LOH on MRI, respectively. Micrometastases (lesion ≤ 2 mm) were seen in only two patients. The average lymph node size on MRI and percentage of patients with FCT were significantly higher in patients with ALN metastasis than in patients without ALN metastasis (p < 0.05).

Table 1 Characteristics of the patients with or without axillary lymph node metastasis
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Fig. 3
figure 3

ROC curves of the clinical prediction models based on the different threshold standards of FCT on MRI, ranging from 1 to 4 mm. The FCT model of 2 mm showed the better AUC of 0.904 (95% confidence interval [CI] 0.847–0.962) than any other model; 0.783 (95% CI 0.718–0.848) of the 1-mm model, 0.660 (95% CI 0.578–0.741) of the 3-mm model, and 0.586 (95% CI 0.522–0.649) of the 4-mm model. AUC area under the curve, FCT focal cortical thickening, MRI magnetic resonance imaging, ROC receiver operating characteristic

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ROC analysis determined optimal cut-off values for Ki-67 grade (≥ 10% vs. < 10%), MRI tumor size (≥ 14 vs. < 14 mm), LAD (≥ 8 vs. < 8 mm), cortical thickness (≥ 4 vs. < 4 mm), and FCT (≥ 2 vs. < 2 mm) (Fig. 3). Table 2 shows the univariate analysis results of each predictor and clinical prediction models established by logistic regression in the derivation cohort. Of the five MRI findings, LOH was not significantly associated with ALN metastasis (p > 0.05). The FCT model had significantly better diagnostic accuracy (AUC = 0.917; 95% confidence interval [CI] 0.869–0.966) than any other model in the derivation cohort (p < 0.05). The cortical thickness model showed the second-best diagnostic performance (AUC = 0.827; 95% CI 0.758–0.896), while the other two models’ AUCs were both below 0.800.

Table 2 Predictors of axillary lymph node metastasis in four clinical predictive models based on magnetic resonance imaging
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Table 3 demonstrates the sensitivity, specificity, positive predictive value (PPV), negative predictive value, and false-negative rate of each predictor on MRI. Of the four prediction models, the MRI FCT model showed the lowest false-negative rate (9%, 3/35). The percentage agreement of FCT on MRI among the 120 cases categorized by two interpreters was 87.5% (105/120), with a kappa coefficient of 0.73 (95% CI 0.60–0.86).

Table 3 Diagnostic performance of each predictor of magnetic resonance imaging
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Discussion

In our study, FCT of ALNs was an independent predictive factor for ALN metastasis of ILC, and the MRI FCT model had the highest accuracy. The new high-sensitivity approach to nodal staging of patients with ILC using MRI FCT may lead to a more accurate nodal burden estimation.

Extensive radiologic research has been conducted to achieve high-accuracy nodal staging in patients with breast cancer [13,14,15,16,17]. Unlike IDC, positron emission tomography/computed tomography is not suitable for nodal staging of ILC because ILC has a lower conspicuity [15]. Of several diagnostic accuracy studies showing detailed ALN morphological features, Kim et al. demonstrated that the cortical thickness-derived parameters (eccentricity, irregularity and LOH of ALNs) were significantly associated with ALN metastasis [17]. However, ILC accounted for less than 5% of cases in the study cohort; therefore, the predictive ability of those parameters for ALN metastasis in patients with ILC has not been fully investigated. Furthermore, the cut-off value of the morphological features of metastatic ALNs was not well-established in the previous literature [11, 13, 18]. In our experience [19], the presence of LOH caused by metastasis cannot be judged when ALNs are smaller than 4 mm in long-axis diameter. Moreover, as most normal ALNs smaller than 4 mm show a round shape, we measured all ALNs that were at least 3 mm in long-axis diameter, and tried to interpret the cortex structure as closely as possible.

The finding of LOH, namely the ‘hilar mass effect’ on US, is reportedly caused by the expansive growth of nodular metastatic foci into the fatty sinusoid space and has been widely accepted as a typical metastatic lymph node finding [20, 21]. However, in our analysis, LOH was not detected in 73% of metastatic ALNs in ILC. Similarly, a recent retrospective study showed that the metastatic ALN exhibited diffuse cortical thickening without a hilar mass effect on US in 68.9% of patients with ILC vs. 28.8% of patients with IDC [4]. The detailed molecular mechanism of this difference is unclear; however, considering that nodular metastatic patterns were observed in approximately the same proportion (approximately 70%) of node-positive IDCs and ILCs on histopathologic examination [22], an expansive growth into the sinusoid by nodular metastatic foci might be less likely to occur in ILC than in IDC due to ILC non-cohesive and migratory properties. This discrepancy in metastatic patterns between IDC and ILC may contribute to the highly sensitive MRI detection of ALN metastasis of ILC. In IDC, it is difficult to recognize the changes in cortical contour and thickness in detail because LOH is frequently detected in the metastatic ALNs of these patients, and lymph nodes with LOH are visualized as round or oval homogeneous hyperintense lesions on T1-weighted MRI in clinical practice [23]. Unfortunately, LOH is also observed in reactive lymph nodes; therefore, it may contribute to false-positive results. Additionally, the difference in the prevalence rate of the LOH metastatic pattern in ALNs between IDC and ILC may be one of the factors influencing the false-positive result of the two subtypes in breast MRI findings.

FCT finding, which is non-uniform cortical thickening showing single or multiple bulges, is the key feature of this analysis. It had the highest sensitivity (88%) and specificity (91%) for ALN metastasis of ILC among all predictors. FCT is caused by scattered metastatic foci in the cortex and is either concentric or eccentric. Paish et al. previously demonstrated that the metastatic growth in the lymph nodes of patients with breast cancer was divided into three patterns: nodular, diffuse, and sinusoidal [23]. The FCT can be masked only when the sinusoidal pattern is predominant because nodular and diffuse patterns are both likely to show an apparent morphological change in the cortex of ALNs, such as FCT. A previous retrospective study that compared the proportions of metastatic growth patterns between IDC and ILC revealed that no metastatic ALN exhibited a sinusoidal pattern in 27 patients with ILC [22]. The high diagnostic accuracy of the FCT model that we used in our analysis may be attributed to this distinct metastatic growth pattern in the lymph nodes of patients with ILC.

Here, nodal FCT-oriented MRI assessment achieved higher accuracy and a drastically lower false-negative rate than in a previous study [24,25,26]. In previous studies, the positive diagnostic criteria of metastatic ALNs in ILC using MRI and US have included both LOH imaging features and cortical thickness as they were used in IDC. To our knowledge, the cortical thickness change of ALNs in ILC has not been investigated in detail. In our analysis, using ROC analysis, FCT was defined as ALN with a cortical thickness change ≥ 2 mm; this may be the most important MRI finding for predicting ALN metastasis of ILC, and the detailed information of cut-off value was not previously reported in literature. Our findings may have important implications for axillary ILC management in clinical settings. Previous studies have reported that ILC is subtle on preoperative imaging, and that metastatic ALNs of ILC are fewer and smaller than those of IDC [4, 24]. Based on our results, by carefully observing the changes in cortical thickness and contour during MRI interpretation, false-negative results may be reduced. If FCT is present on MRI, a second-look US and sequential ALN biopsy targeting FCT should be performed to avoid underestimating nodal burden. This information is helpful for most clinicians, including surgeons, oncologists, and pathologists, since missing locally advanced cancer may result in poor clinical outcomes, and ILC histology is associated with a significantly frequent underestimation of the nodal burden in surgical pathology [27].

Accurate nodal staging might improve the clinical outcome of patients with ILC by reducing the undertreatment; however, the literature on the benefits of neoadjuvant chemotherapy for node-positive ILCs is conflicting [28,29,30]. Considering that most ILCs are luminal A-like type tumors with low histological grades and mitotic activities, a poorer response to neoadjuvant chemotherapy than IDCs seems biologically plausible [31]. Endocrine therapy generally shows lower rates of serious adverse events than chemotherapy, whereas the overall survival benefit of neoadjuvant endocrine therapy for patients with node-positive ILC was reported to be non-inferior to that of neoadjuvant chemotherapy [32]. Although the treatment benefit of neoadjuvant systemic therapy may be limited for ILC, accurate nodal upstaging before surgery can expand treatment options. For example, neoadjuvant therapy may be safely followed with sentinel lymph node biopsy [33] or omission of ALN dissection in certain populations [34].

Our study had several limitations. Firstly, this was a single-institution retrospective study with a small sample size, and the findings should be externally validated in future analyses. Secondly, the number of patients with human epidermal growth factor receptor 2-positive or triple-negative breast cancers was very small due to the history of neoadjuvant chemotherapy, which makes it difficult to directly compare pathological findings with imaging findings. Thirdly, we could not ensure that the surgically resected ALNs showed specific features such as FCT or LOH, because the only preoperative marking techniques for the ALNs used were the radioisotope and dyeing methods for sentinel lymph node biopsy. Finally, in a clinical setting, US-guided fine-needle aspiration is frequently performed to get the pathological diagnosis before operation. Therefore, future prospective, comparative diagnostic test accuracy studies focusing on US FCT are needed to make MRI FCT more clinically useful.

In conclusion, our MRI-detected FCT-focused clinical prediction model demonstrated an excellent diagnostic accuracy for ALN metastases of ILC. In MRI interpretation, close observation of the contour and thickness change of the cortex is important to avoid underestimation of the nodal burden in patients with ILC; however, further external validation studies in clinical settings are required.