AURS–Basic Calculator User Guide

Version: 1.0 (April 2025)

Axillary Ultrasound Risk Score (Basic)

👥 Authors & Contributors

Interactive web calculator for preoperative risk stratification of axillary lymph node (ALN) metastasis in early breast cancer, based on routine B-mode and Doppler ultrasound parameters and clinicopathological features. Freely available at: AxRisk.net.

📖 Background

AURS–Basic is a low-resource, point-based nomogram derived from a systematic evidence synthesis of 35 studies (2015–2025) to predict ALN metastasis in cT1–T2N0 breast cancer using only routine ultrasound markers and clinical data. By integrating 24 high-impact predictors—such as cortical thickness, hilum status, CH ratio, and Doppler indices—the model achieves an AUC of 0.81–0.85 without requiring advanced imaging modalities (MRI, CEUS, SWE).

📚 Methodology & Resources

AURS–Basic was developed through a PRISMA-guided systematic review of 35 studies (2015–2025) evaluating B-mode and Doppler ultrasound markers for axillary lymph node metastasis. The point-based scoring system is grounded in published odds ratios and AUC values, and internal validation on 100 cases demonstrated an AUC of 0.81–0.85.

Code & Data Archive: The code and sample data (v1.0) are available on GitHub and permanently archived on Zenodo (DOI: 10.5281/zenodo.15288756).

🚀 Installation

  1. Clone repository
    git clone https://github.com/yourname/aurbasic.git
cd aurbasic
  2. File structure
    /project-root
├── index.html      ← main calculator UI + logic
├── LICENSE         ← Apache License 2.0 text
└── README.html     ← this user guide
  3. Serve locally (optional)
    # Using Python 3
python -m http.server 8000
# Open http://localhost:8000 in your browser

🎯 Usage

  1. Open index.html in a modern browser (Chrome, Firefox, Safari).
  2. Enter quantitative values:
  3. Click Calculate RI / PI and Calculate CH Ratio to auto-fill indices.
  4. Select applicable morphological and clinical checkboxes.
  5. Press Calculate Risk to display:

⚙️ Input Parameters & Scoring

ParameterThreshold / ConditionPoints
Cortical thickness≥ 4 mm / ≥ 3 mm25 / 15
Short axis≥ 7 mm / ≥ 5 mm20 / 15
L/S ratio< 215
Absent fatty hilumYes20
≥ 3 abnormal lymph nodesYes30
RI> 0.7515
PI> 1.815
CH Ratio> 1.8520
Histologic grade IIIYes15
Tumor size > 2 cmYes10
Skin thickening > 2.5 mmYes20
BI-RADS category 5Yes15
Screen-detected (asymptomatic)Yes-10
BMI ≥ 30 (obesity)Yes5
… full list in source code

Full criteria adapted from Inkov & Baitchev, 2025.

📊 Risk Categories & Interpretation

Total ScoreCategoryEstimated RiskRecommendation
0–29Minimal< 10%Avoid SLNB; surveillance
30–59Low10–20%Consider SLNB
60–89Moderate20–35%SLNB; possibly additional imaging
90–119Moderately High35–50%Consider MRI/biopsy or ALND
120–149High> 50%ALND; preop multidisciplinary planning
150–189Very High> 70%Likely N2; aggressive therapy
≥ 190Critical> 90%Probable N3; multimodal therapy

📖 References

  1. Yi CB, Ding ZY, Deng J, Ye XH, Chen L, Zong M, et al. Combining the Ultrasound Features of Primary Tumor and Axillary Lymph Nodes Can Reduce False-Negative Rate during the Prediction of High Axillary Node Burden in BI-RADS Category 4 or 5 Breast Cancer Lesions. Ultrasound in Medicine & Biology. 2020 Aug;46(8):1941–8.
    http://dx.doi.org/10.1016/j.ultrasmedbio.2020.04.003
  2. Yang L, Gu Y, Wang B, Sun M, Zhang L, Shi L, et al. A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection. BMC Cancer. 2023 Dec 21;23(1).
    http://dx.doi.org/10.1186/s12885-023-11751-z
  3. Yang L, Zhao X, Yang L, Chang Y, Cao C, Li X, et al. A new prediction nomogram of non-sentinel lymph node metastasis in cT1-2 breast cancer patients with positive sentinel lymph nodes. Scientific Reports. 2024 Apr 26;14(1).
    http://dx.doi.org/10.1038/s41598-024-60198-0
  4. Zhang Z, Jiang Q, Wang J, Yang X. A nomogram model for predicting the risk of axillary lymph node metastasis in patients with early breast cancer and cN0 status. Oncology Letters. 2024 May 30;28(2).
    http://dx.doi.org/10.3892/ol.2024.14478
  5. Guo Q, Dong Z, Jiang L, Zhang L, Li Z, Wang D. Assessing Whether Morphological Changes in Axillary Lymph Node Have Already Occurred Prior to Metastasis in Breast Cancer Patients by Ultrasound. Medicina. 2022 Nov 18;58(11):1674.
    http://dx.doi.org/10.3390/medicina58111674
  6. Stachs A, Thi A, Dieterich M, Stubert J, Hartmann S, Glass Ä, et al. Assessment of Ultrasound Features Predicting Axillary Nodal Metastasis in Breast Cancer: The Impact of Cortical Thickness. Ultrasound International Open. 2015 Jul 28;01(01):E19–24.
    http://dx.doi.org/10.1055/s-0035-1555872
  7. Akissue de Camargo Teixeira P, Chala LF, Shimizu C, Filassi JR, Maesaka JY, de Barros N. Axillary Lymph Node Sonographic Features and Breast Tumor Characteristics as Predictors of Malignancy: A Nomogram to Predict Risk. Ultrasound in Medicine & Biology. 2017 Sep;43(9):1837–45.
    http://dx.doi.org/10.1016/j.ultrasmedbio.2017.05.003
  8. Azmil A, Bansal GJ. Can Nomograms Predict Preoperative Axillary Lymph Node Metastasis in Patients With Breast Cancer to Guide Second Look Ultrasonography? Journal of Ultrasound in Medicine. 2017 Nov 20;37(6):1447–53.
    http://dx.doi.org/10.1002/jum.14485
  9. Wang J, Lu X, Zheng X, Xia C, Li P. Clinical Value of Preoperative Ultrasound Signs in Evaluating Axillary Lymph Node Status in Triple-Negative Breast Cancer. In: Yang DH, editor. Journal of Oncology. 2022 May 14;2022:1–7.
    http://dx.doi.org/10.1155/2022/2590647
  10. Li Y, Han D, Shen C, Duan X. Construction of a comprehensive predictive model for axillary lymph node metastasis in breast cancer: a retrospective study. BMC Cancer. 2023 Oct 24;23(1).
    http://dx.doi.org/10.1186/s12885-023-11498-7
  11. Yu X, Hao X, Wan J, Wang Y, Yu L, Liu B. Correlation between Ultrasound Appearance of Small Breast Cancer and Axillary Lymph Node Metastasis. Ultrasound in Medicine & Biology. 2018 Feb;44(2):342–9.
    http://dx.doi.org/10.1016/j.ultrasmedbio.2017.09.020
  12. Zhang H, Sui X, Zhou S, Hu L, Huang X. Correlation of Conventional Ultrasound Characteristics of Breast Tumors With Axillary Lymph Node Metastasis and Ki‐67 Expression in Patients With Breast Cancer. Journal of Ultrasound in Medicine. 2018 Nov 27;38(7):1833–40.
    http://dx.doi.org/10.1002/jum.14879
  13. Ewing DE, Layfield LJ, Joshi CL, Travis MD. Determinants of False-Negative Fine-Needle Aspirates of Axillary Lymph Nodes in Women with Breast Cancer: Lymph Node Size, Cortical Thickness and Hilar Fat Retention. Acta Cytologica. 2015;59(4):311–4.
    http://dx.doi.org/10.1159/000440797
  14. Lim GH, Teo SY, Allen JC, Chinthala JP, Leong LCH. Determining Whether High Nodal Burden in Early Breast Cancer Patients Can Be Predicted Preoperatively to Avoid Sentinel Lymph Node Biopsy. Journal of Breast Cancer. 2019;22(1):67.
    http://dx.doi.org/10.4048/jbc.2019.22.e8
  15. Wang S, Zhang H, Wang X, Yu J, Zhang Q, Zheng Y, et al. Development and Validation of a Nomogram for Axillary Lymph Node Metastasis Risk in Breast Cancer. Journal of Cancer. 2024;15(18):6122–34.
    http://dx.doi.org/10.7150/jca.100651
  16. Zong Q, Deng J, Ge W, Chen J, Xu D. Establishment of Simple Nomograms for Predicting Axillary Lymph Node Involvement in Early Breast Cancer. Cancer Management and Research. 2020 Mar;12:2025–35.
    http://dx.doi.org/10.2147/cmar.s241641
  17. Nakamura R, Yamamoto N, Miyaki T, Itami M, Shina N, Ohtsuka M. Impact of sentinel lymph node biopsy by ultrasound-guided core needle biopsy for patients with suspicious node positive breast cancer. Breast Cancer. 2017 Jul 22;25(1):86–93.
    http://dx.doi.org/10.1007/s12282-017-0795-7
  18. Wang X, Yi X, Zhang Q, Wang X, Zhang H, Peng S, et al. Incorporating ultrasound-based lymph node staging significantly improves the performance of a clinical nomogram for predicting preoperative axillary lymph node metastasis in breast cancer. Biomolecules and Biomedicine. 2023 Jan 13.
    http://dx.doi.org/10.17305/bb.2022.8564
  19. Jamaris S, Jamaluddin J, Islam T, See MH, Fadzli F, Rahmat K, et al. Is pre-operative axillary ultrasound alone sufficient to determine need for axillary dissection in early breast cancer patients? Medicine. 2021 May 14;100(19):e25412.
    http://dx.doi.org/10.1097/md.0000000000025412
  20. Han P, Yang H, Liu M, Cheng L, Wang S, Tong F, et al. Lymph Node Predictive Model with in Vitro Ultrasound Features for Breast Cancer Lymph Node Metastasis. Ultrasound in Medicine & Biology. 2020 Jun;46(6):1395–402.
    http://dx.doi.org/10.1016/j.ultrasmedbio.2020.01.030
  21. Choong WL, Evans A, Purdie CA, Wang H, Donnan PT, Lawson B, et al. Mode of presentation and skin thickening on ultrasound may predict nodal burden in breast cancer patients with a positive axillary core biopsy. British Journal of Radiology. 2020 Jan 28;93(1108).
    http://dx.doi.org/10.1259/bjr.20190711
  22. Dobruch-Sobczak K, Szlenk A, Gumowska M, Mączewska J, Fronczewska K, Łukasiewicz E, et al. Multiparametric ultrasound assessment of axillary lymph nodes in patients with breast cancer. Scientific Reports. 2024 Oct 4;14(1).
    http://dx.doi.org/10.1038/s41598-024-73376-x
  23. Li L, Zhao J, Zhang Y, Pan Z, Zhang J. Nomogram based on multiparametric analysis of early-stage breast cancer: Prediction of high burden metastatic axillary lymph nodes. Thoracic Cancer. 2023 Nov 2;14(35):3465–74.
    http://dx.doi.org/10.1111/1759-7714.15139
  24. Ferroni G, Sabeti S, Abdus-Shakur T, Scalise L, Carter JM, Fazzio RT, et al. Noninvasive prediction of axillary lymph node breast cancer metastasis using morphometric analysis of nodal tumor microvessels in a contrast-free ultrasound approach. Breast Cancer Research. 2023 Jun 9;25(1).
    http://dx.doi.org/10.1186/s13058-023-01670-z
  25. Zheng B, Chen Q. Novel model based on ultrasound predict axillary lymph node metastasis in breast cancer. BMC Medical Imaging. 2023 Sep 18;23(1).
    http://dx.doi.org/10.1186/s12880-023-01090-7
  26. Loonis AST, Chesebro AL, Bay CP, Portnow LH, Weiss A, Chikarmane SA, et al. Positive predictive value of axillary lymph node cortical thickness and nodal, clinical, and tumor characteristics in newly diagnosed breast cancer patients. 2023 Aug 30.
    http://dx.doi.org/10.21203/rs.3.rs-3235615/v1
  27. Aladag Kurt S, Kayadibi Y, Onur I, Uslu Besli L, Necati Sanli A, Velidedeoglu M. Predicting axillary nodal metastasis based on the side of asymmetrical cortical thickening in breast cancer: Evaluation with grayscale and microvascular imaging findings. European Journal of Radiology. 2023 Jan;158:110643.
    http://dx.doi.org/10.1016/j.ejrad.2022.110643
  28. Laiq T, Masood Z, Siddiqui H, Javaid M, Akhtar Mallick MJ. Prediction of axillary lymph node metastasis in breast cancer patients based on ultrasonograhic-clinicopathologic features. Pakistan Journal of Medical Sciences. 2024 Dec 24;41(1):96–100.
    http://dx.doi.org/10.12669/pjms.41.1.10384
  29. Jin H. Prediction of axillary lymph node metastasis in breast cancer using an ultrasonic feature- and clinical data-based model. American Journal of Cancer Research. 2024;14(12):5987–98.
    http://dx.doi.org/10.62347/vtew9920
  30. Bi J. Predictive value of ultrasound assessment of axillary and brachial artery parameters for lymph node metastasis in breast cancer patients. American Journal of Cancer Research. 2025;15(3):1066–80.
    http://dx.doi.org/10.62347/ebei7017
  31. Lim GH, Upadhyaya VS, Acosta HA, Lim JMA, Allen JC, Leong LCH. Preoperative predictors of high and low axillary nodal burden in Z0011 eligible breast cancer patients with a positive lymph node needle biopsy result. European Journal of Surgical Oncology. 2018 Jul;44(7):945–50.
    http://dx.doi.org/10.1016/j.ejso.2018.04.003
  32. Saffar B, Bennett M, Metcalf C, Burrows S. Retrospective preoperative assessment of the axillary lymph nodes in patients with breast cancer and literature review. Clinical Radiology. 2015 Sep;70(9):954–9.
    http://dx.doi.org/10.1016/j.crad.2015.04.019
  33. Imai N, Kitayama M, Shibahara A, Bessho Y, Shibusawa M, Noro A, et al. Strategy for the accurate preoperative evaluation of the number of metastatic axillary lymph nodes in breast cancer. Asian Journal of Surgery. 2019 Jan;42(1):228–34.
    http://dx.doi.org/10.1016/j.asjsur.2018.03.003
  34. Dihge L, Grabau DA, Rasmussen RW, Bendahl PO, Rydén L. The accuracy of preoperative axillary nodal staging in primary breast cancer by ultrasound is modified by nodal metastatic load and tumor biology. Acta Oncologica. 2016 Apr 6;55(8):976–82.
    http://dx.doi.org/10.3109/0284186x.2016.1146826
  35. Qiu SQ, Aarnink M, van Maaren MC, Dorrius MD, Bhattacharya A, Veltman J, et al. Validation and update of a lymph node metastasis prediction model for breast cancer. European Journal of Surgical Oncology. 2018 May;44(5):700–7.
    http://dx.doi.org/10.1016/j.ejso.2017.12.008

Please cite the nomogram as (unpublished):
Inkov I, Baitchev G. AURS–Basic Calculator: A Low-Resource Ultrasound-Based Nomogram for Preoperative Axillary Risk Stratification (Version 1.0) [Software]. Zenodo; 2025. DOI:10.5281/zenodo.15288756.

Further reading: AxRisk.net

📄 License

Calculator v1.0 • April 2025 • Contact: inkov@breastunit.bg

This project is licensed under the Apache License 2.0. See LICENSE for details.

📬 Contact

Dr. Ivan Inkov
Email: inkov@breastunit.bg

Guide generated on April 25, 2025 (Europe/Sofia timezone).