Classification of abnormal findings on ring-type dedicated breast PET for detecting breast cancer

Date 30 September 2019
Event ESMO 2019 Congress
Session Poster Display session 3
Topics Imaging
Breast Cancer
Presenter Shinsuke Sasada
Citation Annals of Oncology (2019) 30 (suppl_5): v574-v584. 10.1093/annonc/mdz257
Authors S. Sasada, N. masumoto, M. Nishina, Y. Kimura, A. Amioka, T. Itagaki, A. Emi, T. Kadoya, M. Okada
  • Surgical Oncology, Institute of Biomedical & Health Sciences, Hiroshima University, 734-8551 - Hiroshima/JP

Abstract

Background

Ring-type dedicated breast positron emission tomography (DbPET) can detect small breast cancers; however, there are no category classifications of abnormal findings on DbPET such as BI-RADs (mammography, ultrasonography, and magnetic resonance imaging). We investigated whether the classification of DbPET findings was useful for detecting breast cancer.

Methods

A total of 674 patients with breast cancers underwent ring-type DbPET using FDG before treatment between January 2016 and March 2019. Findings were morphologically categorized as a focus (uptake size ≤5 mm), mass (>6 mm), or non-mass (multiple uptakes). Non-mass uptakes were additionally classified based on the distribution: focal, linear, regional, segmental, and diffuse. Maximum standardized uptake value (SUVmax) and tumor-to-normal tissue ratio (TNR) were calculated. The final diagnosis was pathologically evaluated based on biopsy or surgical specimens, and lesions of category 2 or lower by conventional examinations were determined benign.

Results

Among 867 abnormal findings, 668 (77%) were malignant and 199 (23%) were benign. Morphologically, 187 (21.6%) lesions were foci, 413 (47.6%) were masses, and 267 (30.8%) were non-masses. Among non-mass lesions, 131 focal, 1 linear, 15 regional, 115 segmental, and 5 diffuse distributions were presented. The median SUVmax was 5.0 and TNR was 2.8. The area under the curve values of SUVmax and TNR for predicting malignancy were 0.824 and 0.855, respectively. In a multivariate analysis, mass, focal and segmental distributions of non-mass lesions, high TNR were significantly related with breast cancer (all P < 0.001). Pathologically confirmed benign lesions included 45 mastopathies, 29 papillomas, 10 fibroadenomas, 7 ductal adenomas, and 3 others.

Conclusions

Classification using morphological findings and TNRs on DbPET are useful to detect breast cancer. The DbPET classification should be considered for breast cancer screening.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.