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  1. OncologyPRO
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  3. ESMO 2018 Congress

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

927 - Predictive models for CEUS of the breast: Is it feasible in improved performance of BI-RADS evaluation of critical breast lesions?

Date

20 Oct 2018

Session

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

Topics

Staging and Imaging

Tumour Site

Breast Cancer

Presenters

Luo Jun

Citation

Annals of Oncology (2018) 29 (suppl_8): viii479-viii482. 10.1093/annonc/mdy294

Authors

L. Jun1, Q. Chen2, L. Tang3, L. Yang4, E. Han5, Y. Chen6, L. Yuan7

Author affiliations

  • 1 Ultrasound Department, Sichuan Provincial People's Hospital, 610000 - Chengdu/CN
  • 2 Ultrasound Department, Sichuan Provincial People's Hospital, 86 - Chengdu/CN
  • 3 Ultrasound Department, Fujian Provincial Cancer Hospital, 8686 - Fuzhou/CN
  • 4 Ultrasound Department, Yunnan Tumor Hospital Third Affiliated Hospital of Kunming Medical University, 86 - Kunming/CN
  • 5 Ultrasound Department, Huangshi Central Hospital, 86 - Huangshi/CN
  • 6 Ultrasound Department, Chengdu First People's Hospital, 86 - Chengdu/CN
  • 7 Ultrasound Department, Tangdu Hospital, 86 - Xian/CN

Resources

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Abstract 927

Background

This prospective study is to determine whether predictive model for contrast-enhanced ultrasound (CEUS) of the breast can improve the precision of BI-RADS.

Methods

A total of 1060 breast lesions classified as BI-RADS 4 or 5 on ultrasound were evaluated. CEUS was performed before core needle biopsy or surgical resection and a revised BI-RADS classification was assigned based on 6 predictive models for CEUS of malignant and benign breast lesions as follows: malignant predictive models : (1) hyper-enhancement with enlarged size; (2) hyper-enhancement with perfusion defect; (3) hyper- or iso-enhancement, present penetrating vessels or crab claw-like pattern. Benign predictive models: (4) rapid wash-in with hyper-enhancement, clear margin after enhancement without enlarged size; (5) synchronous or slow wash-in with iso-enhancement, and cannot distinguish margin and shape after enhancement; and (6) synchronous or slow wash-in with hypo-enhancement, with equal or smaller size after enhancement. To evaluate the diagnostic performance of CEUS-based BI-RADS assignment with pathological examination as reference criteria.

Results

The CEUS-based BI-RADS evaluation classified 287/1060 (27.08%) lesions into category 3, 195 (18.40%), 124 (11.7%) and 144 (13.58%) lesions into categories 4A, 4B and 4C, respectively, and 310 (29.24%) into category 5, compared with 423/1060(39.91%), 348(32.83%), 150(14.15%) and 139(13.11%) in BI-RADS 4A, 4B, 4C. and 5 based on conventional ultrasound and mammography. Selecting CEUS- based BI-RADS category 3 as an appropriate cut-off gave accuracy, sensitivity, specificity, positive and negative predictive values of 69.25%, 98.06%, 49.47%, 58.99% and 96.86%, respectively for the diagnosis of malignant disease. The cancer-to-biopsy yield was 60.16% with CEUS-based BI-RADS 3 selected as the biopsy threshold compared with 43.86% otherwise, while the biopsy rate was only 72.92% compared with 100% otherwise (Figure 2). Overall, only 1.94% of invasive cancers were misdiagnosed as BI-RADS 3 we use nowadays.

Conclusions

This study suggests that evaluation of BI-RADS 4 or 5 breast lesions with CEUS result in reduced biopsy rates and increased cancer-to-biopsy yields.

Clinical trial identification

2016-14-1 release date: 9/9/2016.

Legal entity responsible for the study

Ultrasound Department of Sichuan Provincial People's Hospital.

Funding

Has not received any funding.

Editorial Acknowledgement

Disclosure

All authors have declared no conflicts of interest.

Resources from the same session

5189 - Vall d’Hebron Institute of Oncology (VHIO) Immuno-Oncology prognostic index (VIO): a new tool for improved patient (pt) selection in Phase 1 (Ph1) trials with Immune Checkpoint Inhibitors (ICI).

Presenter: Cinta Hierro

Session: Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

Resources:

Abstract

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