This single-institution study was approved by the institutional review board and ethics committee of our institute in accordance with the Declaration of Helsinki; written informed consent was obtained from each patient for access to their data.
Ring-shaped dbPET scanner
The ring-shaped dbPET scanner (Elmammo, Shimadzu Corp., Kyoto, Japan) consists of 36 detector modules arranged in three contiguous rings, has a diameter of 195 mm and an axial length of 156.5 mm, and has depth-of-interaction measurement capability [15]. The transaxial effective field-of-view (FOV) is 185 mm. Each detector block consists of a four-layered 32 × 32 array of lutetium oxyorthosilicate crystals coupled to a 64-channel positron-sensitive photomultiplier tube via a light guide. Attenuation correction was calculated using a uniform attenuation map with object boundaries obtained from emission data [16]. Scatter correction was performed using the convolution-subtraction method [17] with kernels obtained by background tail fitting. The characteristics and standard performance of this scanner have been reported in detail previously [13].
Whole-body PET/CT scanner
PET/CT scans were obtained using a Biograph Horizon TrueV FDG-PET/CT system (Siemens Medical Solutions, Knoxville, TN, USA). This system has 52 detector rings consisting of 160 blocks, with each block containing an array of 13 × 13 lutetium oxyorthosilicate crystals (4 mm × 4 mm × 20 mm) covering an axial FOV of 221 mm and a transaxial FOV of 690 mm. A CT scan was performed for attenuation correction (130 kV; 15–70 mA; tube rotation time, 0.6 s per rotation; pitch, 1; a transaxial FOV, 700 mm; and section thickness, 5 mm).
Development and preparation of the breast phantom
A cylindrical breast phantom containing four plastic spheres of different diameters was used. The inner and outer diameters of the cylinder were 100 mm and 140 mm, respectively, and the height was 170 mm. The diameters of the spheres arranged inside were 5, 7.5, 10, and 16 mm. Spheres smaller than 5 mm in diameter were not used because they could not be detected by PET/CT. Therefore, the detectability of lesions smaller than 5 mm was not evaluated in this study. The cylinder and four spheres were filled with 18F-FDG solution at a sphere-to-background radioactivity ratio of 8:1 in accordance with a previous study [14]. The background radioactivity at the start of data acquisition by dbPET was set to 2.46 kBq/mL. One scan was performed under each condition.
Data acquisition and image reconstruction
The breast phantom was positioned such that the spheres were precisely located in the same axial plane at different positions in the axial field of view. The spheres were positioned at 8 mm, 13 mm, 19.5 mm (1/8 of axial FOV), 39 mm (1/4 of axial FOV), and 78 mm (1/2 or halfway point of the axial FOV) below the top edge of the detector (Figure 1). Since it is unlikely that a breast lesion is located at the bottom edge of the detector, only the chest wall side of the detector was evaluated. Sphere placement at each position in the detector was confirmed visually and by measurement on the image. The dbPET images were reconstructed using a three-dimensional list mode dynamic row-action maximum-likelihood algorithm with one iteration and 128 subsets, a relaxation control parameter of β=20, and a matrix size in the axial view of 236 × 200 × 236 with a post-reconstruction smoothing Gaussian filter (1.17-mm FWHM). Tight or just mode attenuation correction using a uniform attenuation map with object boundaries obtained from the emission data was performed on phantom or clinical dbPET images, respectively. The scatter correction method used was the convolution-subtraction method with kernels obtained by background tail-fitting [17].
The clinical PET/CT images were reconstructed using the ordered subset expectation maximisation method and the time-of-flight (TOF) algorithm with four iterations and 10 subsets. The CT data were resized from a 512 × 512 matrix to a 180 × 180 matrix to match the PET data and construct CT-based transmission maps for attenuation correction of the PET data with a post-reconstruction smoothing Gaussian filter (5 mm FWHM).
Analyses of phantom image quality
Visual analyses of the phantom images were performed using syngo.via VB10 (Siemens Healthcare GmbH, Erlangen, Germany). An experienced nuclear medicine physician and two experienced PET technologists evaluated the hot spheres. Evaluations were performed using the slices displayed in the transverse image slice containing the sphere centres. The images were displayed in an inverse grey scale with a standardised uptake range of 0–6. The 5-mm-diameter hot sphere was visually graded as follows: 2, identifiable; 1, visualised, but similar hot spots observed elsewhere; and 0, not visualised. Spheres with visual scores ≥1.5 were deemed to be detectable. The final score was the mean of the scores from three readers. The visual assessment was performed based on the Japanese guidelines [18]. Physical analysis was also performed using syngo.via VB10. The coefficient of variation of the background (CVbackground), % background variability (%N5mm), % contrast (%QH,5mm), and contrast-to-noise ratio (QH,5mm/N5mm) were calculated. The CVbackground was calculated by evaluation of various regions of interest (ROIs) in the transverse image slice that contained the sphere centres. Ten ROIs with a diameter of 16 mm were placed in the background region in that slice and ±5-mm–adjacent slices (30 ROIs in total).
See formula 1 in the supplementary files.
%QH,5mm, %N5mm, and their ratio (%QH,5mm/N5mm) were also calculated by evaluation of various ROIs. The 12 ROIs that were 5 mm in diameter were placed on the background region in that slice and ±5-mm–adjacent slices (36 ROIs in total). %QH,5mm and %N5mm were used as measures for the image contrast and noise for the sphere, and their ideal values were 100% and 0%, respectively.
See formula 2 and 3 in the supplementary files.
These physical values were calculated according to a previous report [19].
Analysis of human images
Of a total of 202 consecutive women who underwent both dbPET and whole-body PET/CT scans from August 2016 to September 2019, 62 histologically proven breast cancer tumours of 57 women with positive findings on both dbPET and whole-body PET/CT images were included in the study. Patients fasted at least 6 hours prior to administration of 18F-FDG (3 MBq/kg) and were scanned by whole-body PET/CT for 90 s per bed and dbPET for 7 min per breast. Scans were performed at 60- and 90-min post-injection, both in the prone position. The PET/CT and dbPET images were reconstructed using the same conditions as for the phantom images.
All PET images were evaluated separately by two experienced nuclear medicine physicians (with 16 and 7 years of experience in interpreting PET, respectively). Of the 62 lesions, those in which the shortest distance from the detector edge on the chest wall side to the tumour centre was 2 cm or less on the axial image of dbPET were defined as the “peripheral group”; the other lesions were defined as the “non-peripheral group”. Non-mass uptakes, other than focus and mass-like uptakes, were excluded because their quantitative reliability could not be established.
Tumours that were exactly centred in both peripheral and non-peripheral regions and whose volume was equally present in both regions were also excluded.
The quantitative value of PET is known to be affected by the partial volume effect [20]. To account for lesion size bias, propensity matching was performed to compare the peripheral and non-peripheral groups. The non-peripheral group was reorganised such that lesion size matched the peripheral group in a one-to-one correspondence. As a result, 23 lesions in each group (total 46 lesions) were included in the final analysis.
To evaluate lesion detectability in dbPET depending on the position of the tumour, tumour-to-background ratio (TBR) was calculated as follows. First, the smallest spheroid volume of interest (VOI) that just contained the tumour was placed on the monitor. Second, 5-mm-diameter spherical VOIs were placed at 6 locations on the top, bottom, left, right, anterior, and posterior of the tumour, as close as possible to it, in the non-peripheral group. Five VOIs were used in the peripheral group; the posterior VOI was excluded because there was not enough space to place it posterior of the tumour (Figure 2). The TBR was the maximum standardised uptake value (SUVmax) of the VOI on the tumour divided by an average SUVmean of the five (6) VOIs on the background. The TBRs were compared between dbPET and PET/CT images, and the TBR of dbPET was compared between the peripheral and non-peripheral groups. Additionally, the SUVmax and the SUVpeak (maximum average SUV within a 1-cm3 spherical volume) were measured and compared between groups and between devices.
Statistical analysis
A paired t-test was used to compare the TBR of dbPET and whole-body PET/CT for the peripheral and non-peripheral groups, respectively. The Mann–Whitney U test was used to test for differences in TBR on dbPET between peripheral and non-peripheral lesion groups. The correlations between SUVmax and SUVpeak on dbPET and on WB-PET/CT were evaluated using Pearson correlation coefficients. Statistical significance was defined as p<0.05. Additionally, for these PET measurements, interclass correlation coefficients (ICC) were used to evaluate the reliability between readers.