Abstract

The classification according to uptake patterns and metabolic parameters on ring-type dedicated breast positron emission tomography (dbPET) is useful for detecting breast cancer. This study investigated the performance of dbPET for incidental findings that were not detected by mammography and ultrasonography. In 1,076 patients with breast cancer who underwent dbPET, 276 findings were incidentally diagnosed before treatment. Each finding was categorized as focus (uptake size ≤ 5 mm), mass (> 5 mm), or non-mass (multiple uptake) according to uptake patterns. Non-mass uptakes were additionally classified based on their distributions as—linear, focal, segmental, regional, or diffuse. Thirty-two findings (11.6%) were malignant and 244 (88.4%) were benign. Visually, 227 (82.3%) findings were foci, 7 (2.5%) were masses, and 42 (15.2%) were non-masses. Malignant rates of focus, mass, and non-mass were 9.7%, 28.6%, and 19.0%, respectively. In the non-mass findings, 23 were regional and diffuse distributions, and presented as benign lesions. Focus uptake with low lesion-to-background ratio (LBR) and no hereditary risk were relatively low (2.7%) in breast cancer. In multivariate analysis, LBR and hereditary risk were significantly associated with breast cancer (p = 0.006 and p = 0.013, respectively). Uptake patterns, LBR, and hereditary risk are useful for predicting breast cancer risk in incidental dbPET findings.

Highlights

  • The classification according to uptake patterns and metabolic parameters on ring-type dedicated breast positron emission tomography is useful for detecting breast cancer

  • We have previously reported the usefulness of the classification of dedicated breast positron emission tomography (dbPET) findings using uptake patterns and lesionto-background ratio (LBR) for identifying ­malignancies[11]

  • We investigated whether the classification according to uptake patterns and metabolic features is useful for incidental findings on dbPET, including hereditary risk, in breast cancer

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Summary

Introduction

The classification according to uptake patterns and metabolic parameters on ring-type dedicated breast positron emission tomography (dbPET) is useful for detecting breast cancer. We investigated whether the classification according to uptake patterns and metabolic features is useful for incidental findings on dbPET, including hereditary risk, in breast cancer. Uptake pattern Focus Mass Non-mass Linear Focal Segmental Regional Diffuse SUVmax (IQR) Background SUV (IQR) LBR (IQR) Diagnosis Malignant Benign Pathological diagnosis Radiological diagnosis HBOC risk The probabilities of malignant lesions are shown, based on uptake patterns, LBR, and HBOC risk.

Results
Conclusion

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