Predicting axillary lymph node metastasis in breast cancer patients: A radiomics-based multicenter approach with interpretability analysis.

PURPOSE: To develop a MRI-based radiomics model, integrating the intratumoral and peritumoral imaging information to predict axillary lymph node metastasis (ALNM) in patients with breast cancer and to elucidate the model's decision-making process via interpretable algorithms. METHODS: This study included 376 patients from three institutions who underwent contrast-enhanced breast MRI between 2021 and 2023. We used multiple machine learning algorithms to combine peritumoral, intratumoral, and radiological characteristics with the building of radiological, radiomics, and combined models. The model's performance was compared based on the area under the curve (AUC) obtained from the receiver operating characteristic analysis and interpretable machine learning techniques to analyze the operating mechanism of the model. RESULTS: The radiomics model, incorporating features from both intratumoral tissue and the 3 mm peritumoral region and utilizing the backpropagation neural network (BPNN) algorithm, demonstrated superior diagnostic efficacy, achieving an AUC of 0.820. The AUC of the combination of the RAD score, clinical T stage, and spiculated margin was as high as 0.855. Furthermore, we conducted SHapley Additive exPlanations (SHAP) analysis to evaluate the contributions of RAD score, clinical T stage, and spiculated margin in ALNM status prediction. CONCLUSIONS: The interpretable radiomics model we propose can better predict the ALNM status of breast cancer and help inform clinical treatment decisions.

Investigation of synthetic MRI with quantitative parameters for discriminating axillary lymph nodes status in invasive breast cancer.

OBJECTIVE: To investigate the potential value of quantitative parameters derived from synthetic magnetic resonance imaging (syMRI) for discriminating axillary lymph nodes metastasis (ALNM) in breast cancer patients. MATERIALS AND METHODS: A total of 56 females with histopathologically proven invasive breast cancer who underwent both conventional breast MRI and additional syMRI examinations were enrolled in this study, including 30 patients with ALNM and 26 with non-ALNM. SyMRI has enabled quantification of T1 relaxation time (T1), T2 relaxation time (T2) and proton density (PD). The syMRI quantitative parameters of breast primary tumors before (T1tumor, T2tumor, PDtumor) and after (T1+tumor, T2+tumor, PD+tumor) contrast agent injection were obtained. Similarly, measurements were taken for axillary lymph nodes before (T1LN, T2LN, PDLN) and after (T1+LN, T2+LN, PD+LN) the injection, then theΔT1 (T1-T1+), ΔT2 (T2-T2+), ΔPD (PD-PD+), T1/T2 and T1+/T2+ were calculated. All parameters were compared between ANLM and non-ALNM group. Intraclass correlation coefficient for assessing interobserver agreement. The independent Student's t test or Mann-Whitney U test to determine the relationship between the mean quantitative values and the ALNM. Multivariate logistic regression analyses followed by receiver operating characteristics (ROC) analysis for discriminating ALN status. A P value < 0.05 was considered statistically significant. RESULTS: The short-diameter of lymph nodes (DLN) in ALNM group was significantly longer than that in the non-ALNM group (10.22 ± 3.58 mm vs. 5.28 ± 1.39 mm, P < 0.001). The optimal cutoff value was determined to be 5.78 mm, with an AUC of 0.894 (95 % CI: 0.838-0.939), a sensitivity of 86.7 %, and a specificity of 90.2 %. In syMRI quantitative parameters of breast tumors, T2tumor, ΔT2tumor and ΔPDtumor values showed statistically significant differences between the two groups (P < 0.05). T2tumor value had the best performance in discriminating ALN status (AUC = 0.712), and the optimal cutoff was 90.12 ms, the sensitivity and specificity were 65.0 % and 83.6 % respectively. In terms of syMRI quantitative parameters of lymph nodes, T1LN, T2LN, T1LN/T2LN, T2+LN and ΔT1LN values were significantly different between the two groups (P < 0.05), and their AUCs were 0.785, 0.840, 0.886, 0.702 and 0.754, respectively. Multivariate analyses indicated that the T1LN value was the only independent predictor of ALNM (OR=1.426, 95 % CI: 1.130-1.798, P = 0.039). The diagnostic sensitivity and specificity of T1LN was 86.7 % and 69.4 % respectively at the best cutoff point of 1371.00 ms. The combination of T1LN, T2LN, T1LN/T2LN, ΔT1LN and DLN had better performance for differentiating ALNM and non-ALNM, with AUCs of 0.905, 0.957, 0.964 and 0.897, respectively. CONCLUSION: The quantitative parameters derived from syMRI have certain value for discriminating ALN status in invasive breast cancer, with T2tumor showing the highest diagnostic efficiency among breast lesions parameters. Moreover, T1LN acted as an independent predictor of ALNM.

Challenging Axillary Lymph Nodes on PET/CT in Cancer Patients throughout COVID-19 Vaccination Era.

BACKGROUND: The unexpected detection of axillary lymphadenopathy (AxL) in cancer patients (pts) represents a real concern during the COVID-19 vaccination era. Benign reactions may take place after vaccine inoculation, which can mislead image interpretation in patients undergoing F-18-FDG, F-18-Choline, and Ga-68-DOTATOC PET/CT. They may also mimic loco-regional metastases or disease. We assessed PET/CT findings after COVID-19 first dose vaccination in cancer patients and the impact on their disease course management. METHODS: We evaluated 333 patients undergoing PET/CT (257 F-18-FDG, 54 F-18-Choline, and 23 Ga-68 DOTATOC) scans after the first vaccination with mRNA vaccine (Pfizer-BioNTech) (study group; SG). The uptake index (SUVmax) of suspected AxL was defined as significant when the ratio was > 1.5 as compared to the contralateral lymph nodes. Besides, co-registered CT (Co-CT) features of target lymph nodes were evaluated. Nodes with aggregate imaging positivity were further investigated. RESULTS: Overall, the prevalence of apparently positive lymph nodes on PET scans was 17.1% during the vaccination period. 107 pts of the same setting, who had undergone PET/CT before the COVID-19 pandemic, represented the control group (CG). Only 3 patients of CG showed reactive lymph nodes with a prevalence of 2.8% (p < 0.001 as compared to the vaccination period). 84.2% of SG patients exhibited benign characteristics on co-CT images and only 9 pts needed thorough appraisal. CONCLUSION: The correct interpretation of images is crucial to avoid unnecessary treatments and invasive procedures in vaccinated cancer pts. A detailed anamnestic interview and the analysis of lymph nodes' CT characteristics, after performing PET/CT, may help to clear any misleading diagnosis.

Axillary ultrasonography for early-stage invasive breast cancer.

BACKGROUND: Among women with early invasive breast cancer and 1-2 positive sentinel nodes, sentinel lymph node biopsy (SLNB) is non-inferior to axillary lymph node dissection (ALND).1-3 However, preoperative axillary ultrasonography (AxUS) may not be sensitive enough to discriminate burden of nodal metastasis in these patients, potentially leading to overtreatment.4-6 This study compares axillary operation rates in patients who did and did not receive preoperative AxUS, assessing its utility and risks for overtreatment. METHODS: This is a retrospective cohort study of patients with clinical T1/T2 breast tumors who were clinically node negative and underwent an axillary operation. RESULTS: Patients who had preoperative AxUS received more ALND compared to patients who did not (5.6% vs. 1.4%, p â€‹< â€‹0.001). There was no significant difference in the number of additional axillary operations following SLNB (2.1% vs. 2.3%, p â€‹= â€‹0.77). CONCLUSION: Eliminating preoperative AxUS is associated with fewer invasive ALND procedures, without increased rate of axillary reoperations.

Nomogram Utilizing ABVS Radiomics and Clinical Factors for Predicting ≤ 3 Positive Axillary Lymph Nodes in HR+ /HER2- Breast Cancer with 1-2 Positive Sentinel Nodes.

BACKGROUND: In HR+ /HER2- breast cancer patients with ≤ 3 positive axillary lymph nodes (ALNs), genomic tests can streamline chemotherapy decisions. Current studies, centered on tumor metrics, miss broader patient insights. Automated Breast Volume Scanning (ABVS) provides advanced 3D imaging, and its potential synergy with radiomics for ALN evaluation is untapped. OBJECTIVE: This study sought to combine ABVS radiomics and clinical characteristics in a nomogram to predict ≤ 3 positive ALNs in HR+ /HER2- breast cancer patients with 1-2 positive sentinel lymph nodes (SLNs), guiding clinicians in genetic test candidate selection. METHODS: We enrolled 511 early-stage breast cancer patients: 362 from A Hospital for training and 149 from B Hospital for validation. Using LASSO logistic regression, primary features were identified. A clinical-radiomics nomogram was developed to predict the likelihood of ≤ 3 positive ALNs in HR+ /HER2- patients with 1-2 positive SLNs. We assessed the discriminative capability of the nomogram using the ROC curve. The model's calibration was confirmed through a calibration curve, while its fit was evaluated using the Hosmer-Lemeshow (HL) test. To determine the clinical net benefits, we employed the Decision Curve Analysis (DCA). RESULTS: In the training group, 81.2% patients had ≤ 3 metastatic ALNs, and 83.2% in the validation group. We developed a clinical-radiomics nomogram by analyzing clinical characteristics and rad-scores. Factors like positive SLNs (OR=0.077), absence of negative SLNs (OR=11.138), lymphovascular invasion (OR=0.248), and rad-score (OR=0.003) significantly correlated with ≤ 3 positive ALNs. The clinical-radiomics nomogram, with an AUC of 0.910 in training and 0.882 in validation, outperformed the rad-score-free clinical nomogram (AUCs of 0.796 and 0.782). Calibration curves and the HL test (P values 0.688 and 0.691) confirmed its robustness. DCA showed the clinical-radiomics nomogram provided superior net benefits in predicting ALN burden across specific threshold probabilities. CONCLUSION: We developed a clinical-radiomics nomogram that integrated radiomics from ABVS images and clinical data to predict the presence of ≤ 3 positive ALNs in HR+ /HER2- patients with 1-2 positive SLNs, aiding oncologists in identifying candidates for genomic tests, bypassing ALND. In the era of precision medicine, combining genomic tests with SLN biopsy refines both surgical and systemic patient treatments.

Incidental Axillary Lymphadenopathy Found on Radiation Planning Computed Tomography.

PURPOSE: The aim of this study was to evaluate the rate of axillary node-positive disease in patients with early breast cancer who had a suspicious axillary lymph node on radiation planning computed tomography (CT). METHODS AND MATERIALS: A retrospective review was conducted of the medical records of all patients with breast cancer who were referred for axillary ultrasound from the radiation unit to the breast imaging unit at the Meirav Breast Center, Sheba Medical Center, from 2012 to 2022. Ethics approval was obtained. Only the records of patients who were referred due to an abnormal axillary lymph node seen on radiation planning CT were further evaluated. RESULTS: During the study period, a total of 21 patients were referred to the breast imaging unit for evaluation of suspicious nodes seen on radiation planning CT. Of these, 3 cases were excluded. A total of 15 out of the 18 (83%) patients included had an abnormal lymph node in the ultrasound, and an ultrasound-guided biopsy was recommended (BI-RADS 4). Of these, 3 (out of 15, 20%) had a positive biopsy for tumor cells from the axillary lymph node. Two were cases after primary systemic therapy without complete pathologic response. Thickening of the lymph node cortex and complete loss of the central fatty hilum were associated with pathologic lymph node. CONCLUSION: Sonar had limited ability to differentiate reactive nodes from involved nodes. The presence of lymph nodes with loss of cortical-hilum differentiation on ultrasound together with clinical features are parameters that can help guide the need of further biopsy. Histopathology evaluation is important to make the diagnosis of residual axillary disease. Future studies and guidelines are needed to improve the diagnostic abilities and reduce the number of patients who are undergoing biopsy for noninvolved nodes.

Automated Versus Handheld Breast Ultrasound for Evaluating Axillary Lymph Nodes in Patients With Breast Cancer.

OBJECTIVE: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. MATERIALS AND METHODS: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017-May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. RESULTS: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS-HHUS agreement was 95.9% (236/246; Cohen's kappa = 0.883). CONCLUSION: Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

Solitary Axillary Lymph Node Metastasis From Bladder Cancer Detected by FDG PET/CT.

ABSTRACT: Solitary axillary lymph node metastasis from bladder cancer is rare. A 65-year-old woman with a history of bladder urothelial carcinoma presented to our hospital with an axillary mass. No abnormal lesion in FDG PET/CT was identified except a solitary soft tissue mass with significant FDG uptake in the right axilla. Puncture pathology of the mass confirmed the metastasis of differentiated urothelial carcinoma.

Combined conventional ultrasonography with clinicopathological features to predict axillary status after neoadjuvant therapy for breast cancer: A case-control study.

OBJECTIVES: This study aimed to evaluate the value of a model combining conventional ultrasonography and clinicopathologic features for predicting axillary status after neoadjuvant therapy in breast cancer. METHODS: This retrospective study included 329 patients with lymph node-positive who underwent neoadjuvant systemic treatment (NST) from June 2019 to March 2022. Ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes were analyzed before and after NST. The diagnostic efficacy of ultrasound, clinicopathological characteristics, and combined model were evaluated using multivariate logistic regression and receiver operator characteristic curve (ROC) analyses. RESULTS: The area under ROC (AUC) for the ability of the combined model to predict the axillary pathological complete response (pCR) after NST was 0.882, that diagnostic effectiveness was significantly better than that of the clinicopathological model (AUC of 0.807) and the ultrasound feature model (AUC of 0.795). In addition, eight features were screened as independent predictors of axillary pCR, including clinical N stage, ERBB2 status, Ki-67, and after NST the maximum diameter reduction rate and margins of breast lesions, the short diameter, cortical thickness, and fatty hilum of lymph nodes. CONCLUSIONS: The combined model constructed from ultrasound and clinicopathological features for predicting axillary pCR has favorable diagnostic results, which allowed more accurate identification of BC patients who had received axillary pCR after NST. ADVANCES IN KNOWLEDGE: A combined model incorporated ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes demonstrated favorable performance in evaluating axillary pCR preoperatively and non-invasively.

To scan or not to scan: effect of scanning the axilla of all patients undergoing diagnostic breast ultrasound.

BACKGROUND: Breast ultrasonography is a useful modality in patients undergoing diagnostic and screening breast imaging. However, breast ultrasound has a high false positive rate and can be time-consuming to perform. PURPOSE: The purpose of this study was to evaluate the clinical impact of incidental axillary findings found on diagnostic breast ultrasounds at a single multi-site institution that has a standard protocol of scanning the axilla for all breast ultrasound exams. METHODS: All diagnostic breast ultrasounds were retrospectively reviewed from January 2017 to September 2019. Follow-up imaging, relevant clinical history, and pathology results were also reviewed. All positive axillary findings were divided into incidental or non-incidental findings depending on whether there was a direct clinical indication to scan the axilla. Descriptive statistics were performed with a 5% level of significance. RESULTS: Of the 19,695 diagnostic ultrasounds performed during this timeframe, there were 91 (0.5%) incidental axillary findings given a BIRADS category 3 or 4, and none of these findings resulted in the diagnosis of an occult breast cancer. One biopsy-proven SLL/CLL lymphoma was diagnosed that was otherwise clinically occult. CONCLUSION: Routine axillary scanning in all patients undergoing a diagnostic breast ultrasound at a large multi-site institution yields a low rate of incidental findings and has minimal impact on detection of cancer.

Diagnóstico de precisão das lesões mamárias / Accurate diagnosis of breast lesions

PONTOS-CHAVE As lesões mamárias compreendem uma ampla variedade de diagnósticos que apresentam comportamentos diversos. As lesões mamárias podem ser classificadas como lesões benignas, de potencial de malignidade indeterminado (B3), carcinoma in situ e carcinoma invasor. Na era da medicina personalizada, individualizar e obter um diagnóstico preciso faz grande diferença no desfecho final da paciente, principalmente no caso do câncer de mama. Exames de imagem direcionados e de qualidade, métodos de biópsia adequadamente selecionados e análises de anatomopatologia convencional, imuno-histoquímica e até molecular são determinantes no diagnóstico e no manejo das pacientes.

Incorporating ultrasound-based lymph node staging significantly improves the performance of a clinical nomogram for predicting preoperative axillary lymph node metastasis in breast cancer.

Models for predicting axillary lymph node metastasis (ALNM) in breast cancer patients are lacking. We aimed to develop an efficient model to accurately predict ALNM. Three hundred fifty-five breast cancer patients were recruited and randomly divided into the training and validation sets. Univariate and multivariate logistic regressions were applied to identify predictors of ALNM. We developed nomograms based on these variables to predict ALNM. The performance of the nomograms was tested using the receiver operating characteristic curve and calibration curve, and a decision curve analysis was performed to assess the clinical utility of the prediction models. The nomograms that included clinical N stage (cN), pathological grade (pathGrade), and hemoglobin accurately predicted ALNM in the training and validation sets (area under the curve [AUC] 0.80 and 0.80, respectively). We then explored the importance of the cN and pathGradesignatures used in the integrated model and developed new nomograms by removing the two variables. The results suggested that the combine-pathGrade nomogram also accurately predicted ALNM in the training and validation sets (AUC 0.78 and 0.78, respectively), but the combine-cN nomogram did not (AUC 0.64 and 0.60, in training and validation sets, respectively). We described a cN-based ALNM prediction model in breast cancer patients, presenting a novel efficient clinical decision nomogram for predicting ALNM.

Review of the Sonographic Features of Interpectoral (Rotter) Lymph Nodes in Breast Cancer Staging.

ABSTRACT: This article reviews the ultrasound evaluation and staging of breast cancer with respect to the involvement of interpectoral (Rotter) lymph nodes. The primary objective is to demonstrate and assess the characteristic sonographic findings of interpectoral (Rotter) lymph nodes to help provide accurate nodal staging information. We aim to provide a comprehensive review and serve as an imaging guide for the identification and evaluation of Rotter lymph nodes. The detection of abnormalities and pathologic features of metastatic axillary nodal disease in the interpectoral region is reviewed, and the impact on clinical management and treatment is discussed. In the radiology literature, there is no comprehensive review of the sonographic appearance and evaluation of Rotter lymph nodes.

Evaluation of a Surgical Navigation System for Localization and Excision of Nonpalpable Lesions in Breast and Axillary Surgery.

Introduction: Elucent Medical has introduced a novel EnVisio™ Surgical Navigation system which uses SmartClips™ that generate a unique electromagnetic signal triangulated in 3 dimensions for real-time navigation. The purpose of this study was to evaluate the efficacy and feasibility of the EnVisio Surgical Navigation system in localizing and excising nonpalpable lesions in breast and axillary surgery. Methods: This pilot study prospectively examined patients undergoing breast and nodal localization using the EnVisio Surgical Navigation system. SmartClips were placed by designated radiologists using ultrasound (US) or mammographic (MMG) guidance. The technical evaluation focused on successful deployment and subsequent excision of all localized lesions including SmartClips and biopsy clips. Results: Eleven patients underwent localization using 27 SmartClips which included bracketed multifocal disease (n = 4) and clipped lymph node (n = 1). The bracketed cases were each localized with 2 SmartClips. Mammography and ultrasound were used (n = 8 and n = 19, respectively) to place the SmartClips. All 27 devices were successfully deployed within 5 mm of the targeted lesion or biopsy clip. All SmartClip devices were identified and retrieved intraoperatively. No patients required a second operation for margin excision. Conclusion: In a limited sample, the EnVisio Surgical Navigation system was a reliable technology for the localization of breast and axillary lesions planned for surgical excision. Further comparative studies are required to evaluate its efficacy in relation to the other existing localization modalities.

Accuracy and Utility of Preoperative Ultrasound-Guided Axillary Lymph Node Biopsy for Invasive Breast Cancer: A Systematic Review and Meta-Analysis.

Background: With the acceleration of the pace of life and work, the incidence rate of invasive breast cancer is getting higher and higher, and early diagnosis is very important. This study screened and analyzed the published literature on ultrasound-guided biopsy of invasive breast cancer and obtained the accuracy and practicality of preoperative biopsy. Method: The four databases were screened for the literature. There was no requirement for the start date of retrieval, and the deadline was July 2, 2022. Two researchers screened the literature, respectively, and included the literature on preoperative ultrasound-guided biopsy and intraoperative and postoperative pathological diagnosis of invasive breast cancer. The diagnostic data included in the literature were extracted and meta-analyzed with RevMan 5.4 software, and the bias risk map, forest map, and summary receiver operating characteristic curves (SROC) were drawn. Results: The included 19 studies involved about 18668 patients with invasive breast cancer. The degree of bias of the included literature is low. The distribution range of true positive, false positive, true negative, and false negative in the forest map is large, which may be related to the large difference in the number of patients in each study. Most studies in the SROC curve are at the upper left, indicating that the accuracy of ultrasound-guided axillary biopsy is very high. Conclusion: For invasive breast cancer, preoperative ultrasound-guided biopsy can accurately predict staging and grading of breast cancer, which has important reference value for surgery and follow-up treatment.

MRI Diagnosis and Pathological Examination of Axillary Lymph Node Metastasis in Breast Cancer Patients.

In order to explore the characteristics and diagnostic value of magnetic resonance imaging (MRI) in axillary lymph node metastasis of breast cancer, a total of 200 breast cancer patients diagnosed and treated from January 2021 to January 2022 are selected as the study subjects, and 200 patients are divided into an axillary lymph node metastasis group and a simple breast cancer group according to pathological results. The pathological results are used as the gold standard to determine the accuracy and diagnostic efficacy of MRI results. A multivariate logistic regression method is used to analyze the influencing factors of MRI image characteristics of breast cancer axillary lymph node metastasis. The experimental results show that MRI has high application values in diagnosing axillary lymph node metastasis of breast cancer, which is worthy of clinical promotion and application.

The value of whole-lesion histogram analysis based on field­of­view optimized and constrained undistorted single shot (FOCUS) DWI for predicting axillary lymph node status in early-stage breast cancer.

BACKGROUND: This study aims to estimate the amount of axillary lymph node (ALN) involvement in early-stage breast cancer utilizing a field of view (FOV) optimized and constrained undistorted single-shot (FOCUS) diffusion-weighted imaging (DWI) approach, as well as a whole-lesion histogram analysis. METHODS: This retrospective analysis involved 81 individuals with invasive breast cancer. The patients were divided into three groups: N0 (negative ALN metastasis), N1-2 (low metastatic burden with 1-2 ALNs), and N≥3 (heavy metastatic burden with ≥ 3 ALNs) based on their sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND). Histogram parameters of apparent diffusion coefficient (ADC) depending basically on FOCUS DWI were performed using 3D-Slicer software for whole lesions. The typical histogram characteristics for N0, N1-2, and N≥ 3 were compared to identify the significantly different parameters. To determine the diagnostic efficacy of significantly different factors, the area under their receiver operating characteristic (ROC) curves was examined. RESULTS: There were significant differences in the energy, maximum, 90 percentile, range, and lesion size among N0, N1-2, and N≥ 3 groups (P < 0.05). The energy differed significantly between N0 and N1-2 groups (P < 0.05), and some certain ADC histogram parameters and lesion sizes differed significantly between N0 and N≥3, or N1-2 and N≥3 groups. For ROC analysis, the energy yielded the best diagnostic performance in distinguishing N0 and N1-2 groups from N≥3 group with an AUC value of0.853. All parameters revealed excellent inter-observer agreement with inter-reader consistencies data ranging from0.919 to 0.982. CONCLUSION: By employing FOCUS DWI method, the analysis of whole-lesion ADC histogram quantitatively provides a non-invasive way to evaluate the degree of ALN metastatic spread in early-stage breast cancer.