Effect of radioactivity outside the field of view on image quality of dedicated breast positron emission tomography: preliminary phantom and clinical studies

Satoh, Yoko; Imai, Masamichi; Ikegawa, Chihiro; Hirata, Kenji; Abo, Norifumi; Kusuzaki, Mao; Oyama‐Manabe, Noriko; Oda, Hiroshi

doi:10.1007/s12149-022-01789-7

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…Moreover, referring to the clinical images, the SiPM-based TOF-PET images seemed to have more noise enhanced near the chest wall, especially the 18 F-FDG abnormal accumulation at the left myocardium ( Figure 7 ). The image quality of ring-shaped dbPET images was reported to be degraded at the detector edge due to FDG accumulated in the myocardium and other body parts, although sensitivity correction was performed [ 21 ]. Thus, in SiPM-based TOF-PET with a larger detector surface diameter, radioactivity outside the FOV may have a greater impact.…”

Section: Discussionmentioning

confidence: 99%

Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models

et al. 2023

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The performances of photomultiplier tube (PMT)-based dedicated breast positron emission tomography (PET) and silicon photomultiplier tube (SiPM)-based time-of-flight (TOF) PET, which is applicable not only to breast imaging but also to head imaging, were compared using a phantom study. A cylindrical phantom containing four spheres (3–10 mm in diameter) filled with 18F-FDG at two signal-to-background ratios (SBRs), 4:1 and 8:1, was scanned. The phantom images, which were reconstructed using three-dimensional list-mode dynamic row-action maximum likelihood algorithm with various β-values and post-smoothing filters, were visually and quantitatively compared. Visual evaluation showed that the 3 mm sphere was more clearly visualized with higher β and smaller post-filters, while the background was noisier; SiPM-based TOF-PET was superior to PMT-based dbPET in sharpness, smoothness, and detectability, although the background was noisier at the SBR of 8:1. Quantitative evaluation revealed that the detection index (DI) and recovery coefficient (CRC) of SiPM-based TOF-PET images were higher than those of PMT-based PET images, despite a higher background coefficient of variation (CVBG). The two organ-specific PET systems showed that a 3 mm lesion in the breast could be visualized at the center of the detector, and there was less noise in the SiPM-based TOF-PET image.

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Section: Discussionmentioning

confidence: 99%

Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models

et al. 2023

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“…This increases noise in dbPET images compared with whole-body PET images. These noises are sometimes difficult to distinguish from small lesions and can lead to false-negative or false-positive findings, which affect quantitative PET values such as SUV [ 7 , 24 ]. Increasing the acquisition time and injecting a sufficient FDG dose, which lead to increased patient burden and decreased test efficiency, are necessary to reduce noise.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, dedicated breast PET (dbPET) that specializes in breast imaging has been developed, and basic and clinical studies using dbPET are underway [ 7 , 8 , 9 ]. dbPET can acquire data with higher spatial resolution than whole-body PET, thereby demonstrating higher sensitivity for BC detection [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Proposal to Improve the Image Quality of Short-Acquisition Time-Dedicated Breast Positron Emission Tomography Using the Pix2pix Generative Adversarial Network

et al. 2022

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This study aimed to evaluate the ability of the pix2pix generative adversarial network (GAN) to improve the image quality of low-count dedicated breast positron emission tomography (dbPET). Pairs of full- and low-count dbPET images were collected from 49 breasts. An image synthesis model was constructed using pix2pix GAN for each acquisition time with training (3776 pairs from 16 breasts) and validation data (1652 pairs from 7 breasts). Test data included dbPET images synthesized by our model from 26 breasts with short acquisition times. Two breast radiologists visually compared the overall image quality of the original and synthesized images derived from the short-acquisition time data (scores of 1–5). Further quantitative evaluation was performed using a peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the visual evaluation, both readers revealed an average score of >3 for all images. The quantitative evaluation revealed significantly higher SSIM (p < 0.01) and PSNR (p < 0.01) for 26 s synthetic images and higher PSNR for 52 s images (p < 0.01) than for the original images. Our model improved the quality of low-count time dbPET synthetic images, with a more significant effect on images with lower counts.

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Deep learning model with collage images for the segmentation of dedicated breast positron emission tomography images

Imokawa,

Satoh,

Fujioka

et al. 2023

Breast Cancer

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Effect of radioactivity outside the field of view on image quality of dedicated breast positron emission tomography: preliminary phantom and clinical studies

Cited by 5 publications

References 21 publications

Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models

Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models

Proposal to Improve the Image Quality of Short-Acquisition Time-Dedicated Breast Positron Emission Tomography Using the Pix2pix Generative Adversarial Network

Deep learning model with collage images for the segmentation of dedicated breast positron emission tomography images

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