Evaluation of image quality at the detector’s edge of dedicated breast positron emission tomography

Abstract

Background: We assessed image quality of dedicated breast positron emission tomography (dbPET) at the detector's edge by phantom and clinical studies.Methods: A breast phantom with four spheres (16, 10, 7.5, and 5 mm diameter) was filled with 18F-fluorodeoxyglucose solution (sphere-to-background ratio, 8:1). The spheres occupied five different positions from the top edge to the centre of the detector and were scanned for 5 min in each position. Reconstructed images were visually evaluated, and % background variability (%N5mm), % contrast (%QH,5mm), and contrast-to-noise ratio (QH,5mm/N5mm) for the 5 mm sphere; and coefficient of variation of the background (CVbackground) were calculated. Subsequently, clinical cases were analysed. Tumour-to-background ratios (TBRs) between breast cancer near the chest wall (close to the detector’s edge; peripheral group) and at other locations (non-peripheral group) were compared. The TBR of each lesion was compared between dbPET and PET/computed tomography (CT).Results: Closer to the detector’s edge, the %N5mm and CVbackground increased and %QH,5mm and QH,5mm/N5mm decreased in the phantom study. The disadvantages of this placement were visually confirmed. Regarding clinical images, TBR of dbPET was significantly higher than that of PET/CT in both the peripheral (12.1±6.2 vs. 6.5±3.4, p=0.0001) and non-peripheral (13.1±7.1 vs. 7.7±7.4, p=0.0004) groups. There was no significant difference in TBR of dbPET between the peripheral and non-peripheral groups (12.1±6.2 vs. 13.1±7.1, p=0.6367).Conclusion: The phantom study revealed poorer image quality closer to the detector edge at a depth of 1/8 of the axial field of view (FOV) than at other more central parts. In clinical studies, however, lesion detectability of dbPET was the same regardless of the lesion position, and it was higher than that in PET/CT. dbPET has a great potential for detecting breast lesions near the chest wall if they are within the FOV, even in young women with small breasts.

Pseudo Zernike Moment and Deep Stacked Sparse Autoencoder for COVID-19 Diagnosis

“…CCT is one of the best chest imaging [6] techniques since it provides the finest resolution and can recognize extremely small nodules in the chest region. CCT employs computer-processed combinations of multiple X-ray observations taken from different angles [7] to produce highquality 3D tomographic images (virtual slices). In contrast, CXR only provides one 2D image, which performs poorly on soft tissue contrast.…”