Enhancing precision in bone metastasis diagnosis for lobular breast cancer: reassessing the role of 18F-FDG PET/CT

• Published in: Nuclear medicine communications
• Main Authors: Usmani, Sharjeel, Al Riyami, Khulood, Jain, Anjali, Alajmi, Adil Aljarrah, AlBaimani, Khalid, Dumasig, Paul, Al Busaidi, Asiya, Al Sukati, Rashid
• Format: Journal Article
• Language: English
• Published: England 01.10.2024
• ISSN: 1473-5628
• DOI: 10.1097/MNM.0000000000001880

Detection of osseous metastases by imaging can be challenging in patients with invasive lobular breast cancer (ILC). ILC may demonstrate low metabolic rate due to lower tumor cell density, decreased proliferation rate, diffuse infiltration of surrounding tissue, and low level of GLUT-1 expression. The aim of this study is to assess the diagnostic accuracy of 18F-FDG PET/CT in identifying bone metastases in ILC patients. Out of 52 individuals diagnosed with lobular breast cancer and underwent 18F-FDG PET/CT for evaluation of metastases, 21 patients were included in our study population after applying inclusion and exclusion criteria. The radiological and clinical follow-up of at least 6 months served as the reference standard comparator. Bone metastases were confirmed in six patients. 18F-FDG PET/CT was true positive in two and false negative in four patients. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 18F-FDG PET/CT were 33.33, 93.33, 66.67, 77.78, and 76.19%, respectively (95% confidence interval). The tendency of ILC osseous metastases to be more sclerotic explains the low diagnostic accuracy of 18F-FDG PET/CT in detection of bone metastases, making it a less suited method of evaluation. The results of the present study indicate that 18F-FDG PET/CT has a low diagnostic accuracy in detecting bone metastases in lobular breast cancer and, by inference, new functional modalities can be explored in these patients. The findings contribute valuable insights to optimize the integration of molecular imaging into the diagnostic algorithm for this specific breast cancer subtype.