Can the BMI-based dose regimen be used to reduce injection activity and to obtain a constant image quality in oncological patients by 18F-FDG total-body PET/CT imaging?

Fully automated computational measurement of noise in positron emission tomography

OBJECTIVES

To introduce an automated computational algorithm that estimates the global noise level across the whole imaging volume of PET datasets.

METHODS

[18F]FDG PET images of 38 patients were reconstructed with simulated decreasing acquisition times (15-120 s) resulting in increasing noise levels, and with block sequential regularized expectation maximization with beta values of 450 and 600 (Q.Clear 450 and 600). One reader performed manual volume-of-interest (VOI) based noise measurements in liver and lung parenchyma and two readers graded subjective image quality as sufficient or insufficient. An automated computational noise measurement algorithm was developed and deployed on the whole imaging volume of each reconstruction, delivering a single value representing the global image noise (Global Noise Index, GNI). Manual noise measurement values and subjective image quality gradings were compared with the GNI.

RESULTS

Irrespective of the absolute noise values, there was no significant difference between the GNI and manual liver measurements in terms of the distribution of noise values (p = 0.84 for Q.Clear 450, and p = 0.51 for Q.Clear 600). The GNI showed a fair to moderately strong correlation with manual noise measurements in liver parenchyma (r = 0.6 in Q.Clear 450, r = 0.54 in Q.Clear 600, all p < 0.001), and a fair correlation with manual noise measurements in lung parenchyma (r = 0.52 in Q.Clear 450, r = 0.33 in Q.Clear 600, all p < 0.001). Classification performance of the GNI for subjective image quality was AUC 0.898 for Q.Clear 450 and 0.919 for Q.Clear 600.

CONCLUSION

An algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets.

CLINICAL RELEVANCE STATEMENT

An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking of clinical PET imaging within and across institutions.

KEY POINTS

• Noise is an important quantitative marker that strongly impacts image quality of PET images. • An automated computational noise measurement algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. • An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking as well as protocol harmonization.

Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system

To evaluate whether a machine learning classifier can evaluate image quality of maximum intensity projection (MIP) images from F18-FDG-PET scans. A total of 400 MIP images from F18-FDG-PET with simulated decreasing acquisition time (120 s, 90 s, 60 s, 30 s and 15 s per bed-position) using block sequential regularized expectation maximization (BSREM) with a beta-value of 450 and 600 were created. A machine learning classifier was fed with 283 images rated "sufficient image quality" and 117 images rated "insufficient image quality". The classification performance of the machine learning classifier was assessed by calculating sensitivity, specificity, and area under the receiver operating characteristics curve (AUC) using reader-based classification as the target. Classification performance of the machine learning classifier was AUC 0.978 for BSREM beta 450 and 0.967 for BSREM beta 600. The algorithm showed a sensitivity of 89% and 94% and a specificity of 94% and 94% for the reconstruction BSREM 450 and 600, respectively. Automated assessment of image quality from F18-FDG-PET images using a machine learning classifier provides equivalent performance to manual assessment by experienced radiologists.

Impact of Region-of-Interest Delineation on Stability and Reproducibility of Liver SNR Measurements in 68 Ga-PSMA PET/CT

Objective  This study aims to assess the impact of various regions of interest (ROIs) and volumes of interest (VOIs) delineations on the reproducibility of liver signal-to-noise-ratio (SNRliver) measurements, as well as to find the most reproducible way to estimate it in gallium-68 positron emission tomography ( ⁶⁸ Ga-PET) imaging. We also investigated the SNRliver-weight relationship for these ROIs and VOIs delineations. Methods  A cohort of 40 patients (40 males; mean weight: 76.5 kg [58-115 kg]) with prostate cancer were included. ⁶⁸ Ga-PET/CT imaging (mean injected activity: 91.4 MBq [51.2 MBq to 134.1 MBq] was performed on a 5-ring bismuth germanium oxide-based Discovery IQ PET/CT using ordered subset expectation maximization image reconstruction algorithm. Afterward, circular ROIs and spherical VOIs with two different diameters of 30 and 40 mm were drawn on the right lobe of the livers. The performance of the various defined regions was evaluated by the average standardized uptake value (SUV _mean ), standard deviation (SD) of the SUV (SUV _SD ), SNR _liver , and SD of the SNR _liver metrics. Results  There were no significant differences in SUV _mean among the various ROIs and VOIs ( p  > 0.05). On the other hand, the lower SUV _SD was obtained by spherical VOI with diameter of 30 mm. The largest SNR _liver was obtained by ROI (30 mm). The SD of SNR _liver with ROI (30 mm) was also the largest, while the lowest SD of SNR _liver was observed for VOI (40 mm). There is a higher correlation coefficient between the patient-dependent parameter of weight and the image quality parameter of SNRliver for both VOI (30 mm) and VOI (40 mm) compared to the ROIs. Conclusion  Our results indicate that SNR _liver measurements are affected by the size and shape of the respective ROIs and VOIs. The spherical VOI with a 40 mm diameter leads to more stable and reproducible SNR measurement in the liver.

Impact of patient's habitus on image quality and quantitative metrics in 18F-FDG PET/CT images

PURPOSE

To study how the quantitative parameters of 18F-FDG PET imaging change with the emission scan duration (ESD) and the body-mass-index (BMI) in phantom and patients on a time-of-flight (TOF)-PET/CT system.

METHODS

The image-quality phantom with (b-NEMA-IQ, BMI = 29.2 kg/m²) and without (NEMA-IEC, BMI = 21.4 kg/m²) a 'belt' of water-bags was filled with 18F-FDG activities to obtain nominal standardized uptake values (SUV) of 19, 8 and 5. Patients with BMI ≤ 25 kg/m² (L-BMI) and BMI > 25 kg/m² (H-BMI) were enrolled in this study. Phantom and patients underwent list-mode PET acquisition at 120 s/bed-position. Images reconstructed with clinical protocol and different ESD (120, 90, 75, 60, 45, 30 s) were analysed for comparison of maximum SUV (SUV_max), maximum standardized uptake value lean-body-mass corrected (SUL_max) and noise.

RESULTS

79 oncologic patients (45 L-BMI, 44 H-BMI) were analysed. From 90 s to 30 s, an increasing variation of SUV_max and SUL_max with respect to the reference 120 s time was observed, from 18% to 60% and from 16% to 37% for phantom and patients, respectively. SUV_max values were significantly higher (+50%) in b-NEMA-IQ than NEMA-IQ phantom and in H-BMI (+33%) than L-BMI patients. No significant difference was found in SUL_max for the two BMI categories in both phantom and patients. CV values decreased when increasing ESD, being higher in H-BMI patients (0.13-0.25) and b-NEMA-IQ phantom (0.15-0.28) than in L-BMI patients (0.11-0.21) and NEMA-IQ phantom (0.11-0.20).

CONCLUSIONS

Reduction of ESD may severely impact on the variations of SUV_max and SUL_max in 18F-FDG PET/CT imaging. This study confirms recommendations of using SUL for lesion uptake quantification, being unaffected by BMI variation.

A personal acquisition time regimen of 68Ga-DOTATATE total-body PET/CT in patients with neuroendocrine tumor (NET): a feasibility study

BACKGROUND

The injection activity of tracer, acquisition time, patient-specific photon attenuation, and large body mass, can influence on image quality. Fixed acquisition time and body mass related injection activity in clinical practice results in a large difference in image quality. Thus, this study proposes a patient-specific acquisition time regimen of ⁶⁸ Ga-DOTATATE total-body positron emission tomography-computed tomography (PET/CT) to counteract the influence of body mass (BM, kg) on image quality, and acquire an acceptable and constant image of patients with neuroendocrine tumors (NETs).

METHODS

The development cohort consisting of 19 consecutive patients with full activity (88.7-204.9 MBq, 2.0 ± 0.1 MBq/kg) was to establish the acquisition time regimen. The liver SNR (signal-to-noise ratio, SNR_L) was normalized (SNR_norm) by the product of injected activity (MBq) and acquisition time (min). Fitting of SNR_norm against body mass (BM, kg) in linear correlation was performed. Subjective assessment of image quality was performed using a 5-point Likert scale to determine the acceptable threshold of SNR_L, and an optimized acquisition regimen based on BM was proposed, and validated its feasibility through the validation cohort of 57 consecutive NET patients with half activity (66.9 ± 11.3 MBq, 1.0 ± 0.1 MBq/kg) and a fixed acquisition time regimen.

RESULTS

The linear correlation (R² = 0.63) between SNR_norm and BM (kg) was SNR_norm = -0.01*BM + 1.50. The threshold SNR_L of acceptable image quality was 11.2. The patient-specific variable acquisition time regimen was determined as: t (min) = 125.4/(injective activity)*(-0.01*BM + 1.50)². Based on that proposed regimen, the average acquisition time for acceptable image quality in the validation cohort was 2.99 ± 0.91 min, ranging from 2.18 to 6.35 min, which was reduced by 36.50% ~ 78.20% compared with the fixed acquisition time of 10 min. Subjective evaluation showed that acceptable image quality could be obtained at 3.00 min in the validation group, with an average subjective score of 3.44 ± 0.53 (kappa = 0.97, 95% CI: 0.96 ~ 0.98). Bland-Altman analysis revealed good agreement between the proposed regimen and the fixed acquisition time cohort.

CONCLUSION

A patient-specific acquisition time regimen was proposed in NET patients in development cohort and validated its feasibility in patients with NETs in validation cohort by ⁶⁸ Ga-DOTATATE total-body PET/CT imaging. Based on the proposed regimen, the homogenous image quality with optimal acquisition time was available independent of body mass.

Deep progressive learning achieves whole-body low-dose 18F-FDG PET imaging

Objectives

To validate a total-body PET-guided deep progressive learning reconstruction method (DPR) for low-dose 18F-FDG PET imaging.

Methods

List-mode data from the retrospective study (n = 26) were rebinned into short-duration scans and reconstructed with DPR. The standard uptake value (SUV) and tumor-to-liver ratio (TLR) in lesions and coefficient of variation (COV) in the liver in the DPR images were compared to the reference (OSEM images with full-duration data). In the prospective study, another 41 patients were injected with 1/3 of the activity based on the retrospective results. The DPR images (DPR_1/3(p)) were generated and compared with the reference (OSEM images with extended acquisition time). The SUV and COV were evaluated in three selected organs: liver, blood pool and muscle. Quantitative analyses were performed with lesion SUV and TLR, furthermore on small lesions (≤ 10 mm in diameter). Additionally, a 5-point Likert scale visual analysis was performed on the following perspectives: contrast, noise and diagnostic confidence.

Results

In the retrospective study, the DPR with one-third duration can maintain the image quality as the reference. In the prospective study, good agreement among the SUVs was observed in all selected organs. The quantitative results showed that there was no significant difference in COV between the DPR_1/3(p) group and the reference, while the visual analysis showed no significant differences in image contrast, noise and diagnostic confidence. The lesion SUVs and TLRs in the DPR_1/3(p) group were significantly enhanced compared with the reference, even for small lesions.

Conclusions

The proposed DPR method can reduce the administered activity of 18F-FDG by up to 2/3 in a real-world deployment while maintaining image quality.

The predictive value of total-body PET/CT in non-small cell lung cancer for the PD-L1 high expression

Purpose

Total-body positron emission tomography/computed tomography (PET/CT) provides faster scanning speed, higher image quality, and lower injected dose. To compensate for the shortcomings of the maximum standard uptake value (SUVmax), we aimed to normalize the values of PET parameters using liver and blood pool SUV (SUR-L and SUR-BP) to predict programmed cell death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC) patients.

Materials and methods

A total of 138 (104 adenocarcinoma and 34 squamous cell carcinoma) primary diagnosed NSCLC patients who underwent ¹⁸F-FDG-PET/CT imaging were analyzed retrospectively. Immunohistochemistry (IHC) analysis was performed for PD-L1 expression on tumor cells and tumor-infiltrating immune cells with 22C3 antibody. Positive PD-L1 expression was defined as tumor cells no less than 50% or tumor-infiltrating immune cells no less than 10%. The relationships between PD-L1 expression and PET parameters (SUVmax, SUR-L, and SUR-BP) and clinical variables were analyzed. Statistical analysis included χ² test, receiver operating characteristic (ROC), and binary logistic regression.

Results

There were 36 patients (26%) expressing PD-L1 positively. Gender, smoking history, Ki-67, and histologic subtype were related factors. SUVmax, SUR-L, and SUR-BP were significantly higher in the positive subset than those in the negative subset. Among them, the area under the curve (AUC) of SUR-L on the ROC curve was the biggest one. In NSCLC patients, the best cutoff value of SUR-L for PD-L1-positive expression was 4.84 (AUC = 0.702, P = 0.000, sensitivity = 83.3%, specificity = 54.9%). Multivariate analysis confirmed that age and SUR-L were correlated factors in adenocarcinoma (ADC) patients.

Conclusion

SUVmax, SUR-L, and SUR-BP had utility in predicting PD-L1 high expression, and SUR-L was the most reliable parameter. PET/CT can offer reference to screen patients for first-line atezolizumab therapy.

The feasibility of ultralow-activity 18F-FDG dynamic PET imaging in lung adenocarcinoma patients through total-body PET/CT scanner

OBJECTIVE

To explore the feasibility of ultralow-activity ¹⁸F-FDG total-body dynamic PET imaging for clinical practice in patients with lung adenocarcinoma.

METHODS

Eight of 18 patients were randomly injected with ¹⁸F-FDG with full activity (3.7 MBq/kg) for total-body dynamic PET imaging, while 10 received one-tenth activity (0.37 MBq/kg). The generated time-to-activity curves (TACs) according to the regions of interest (ROIs) were processed by PMOD through standard FDG two-tissue compartment model fitting. The kinetic constant rates (K1, K2, K3, and Ki), radiation dose, prompt counts, and data storage size were analysed between the full- and ultralow-activity groups. The SUVmax-Tumour/SUVmax-Liver and SUVmax-Tumour/SUVmax-Muscle on static PET images were also assessed.

RESULTS

Each of the fitted models has a satisfactory goodness-of-fit with R² greater than 0.9 except 3 (3/234) in ultralow-activity group, where one in pancreas (R² = 0.851), another one in muscle (R² = 0.868), and the third one in bone marrow (R² = 0.895). All the fitted models in the full-activity group had a better goodness-of-fit than those in the ultralow-activity group. However, no significant differences were found in any of the kinetic metrics or image quality between the two groups except in the reduction of radiation dose and data storage size.

CONCLUSIONS

The 10 × reduction of injected ¹⁸F-FDG could achieve comparable kinetic metrics and T/N ratios by total-body dynamic PET imaging in lung adenocarcinoma patients. Ultralow-activity total-body PET imaging is feasible for clinical practice in oncological patients without obesity, especially in dynamic PET scanning.

Expert consensus on oncological [18F]FDG total-body PET/CT imaging (version 1)

BACKGROUND

[¹⁸F]FDG imaging on total-body PET/CT (TB PET/CT) scanners, with improved sensitivity, offers new potentials for cancer diagnosis, staging, and radiation treatment planning. This consensus provides the protocols for clinical practices with a goal of paving the way for future studies with the total-body scanners in oncological [¹⁸F]FDG TB PET/CT imaging.

METHODS

The consensus was summarized based on the published guidelines and peer-reviewed articles of TB PET/CT in the literature, along with the opinions of the experts from major research institutions with a total of 40,000 cases performed on the TB PET/CT scanners.

RESULTS

This consensus describes the protocols for routine and dynamic [¹⁸F]FDG TB PET/CT scanning focusing on the reduction of imaging acquisition time and FDG injected activity, which may serve as a reference for research and clinic oncological PET/CT studies.

CONCLUSION

This expert consensus focuses on the reduction of acquisition time and FDG injected activity with a TB PET/CT scanner, which may improve the patient throughput or reduce the radiation exposure in daily clinical oncologic imaging.

KEY POINTS

• [¹⁸F]FDG-imaging protocols for oncological total-body PET/CT with reduced acquisition time or with different FDG activity levels have been summarized from multicenter studies. • Total-body PET/CT provides better image quality and improved diagnostic insights. • Clinical workflow and patient management have been improved.

Relating18F-FDG image signal-to-noise ratio to time-of-flight noise-equivalent count rate in total-body PET using the uEXPLORER scanner

Objective.This work assessed the relationship between image signal-to-noise ratio (SNR) and total-body noise-equivalent count rate (NECR)-for both non-time-of-flight (TOF) NECR and TOF-NECR-in a long uniform water cylinder and 14 healthy human subjects using the uEXPLORER total-body PET/CT scanner.Approach.A TOF-NEC expression was modified for list-mode PET data, and both the non-TOF NECR and TOF-NECR were compared using datasets from a long uniform water cylinder and 14 human subjects scanned up to 12 h after radiotracer injection.Main results.The TOF-NECR for the uniform water cylinder was found to be linearly proportional to the TOF-reconstructed image SNR²in the range of radioactivity concentrations studied, but not for non-TOF NECR as indicated by the reducedR²value. The results suggest that the use of TOF-NECR to estimate the count rate performance of TOF-enabled PET systems may be more appropriate for predicting the SNR of TOF-reconstructed images.Significance.Image quality in PET is commonly characterized by image SNR and, correspondingly, the NECR. While the use of NECR for predicting image quality in conventional PET systems is well-studied, the relationship between SNR and NECR has not been examined in detail in long axial field-of-view total-body PET systems, especially for human subjects. Furthermore, the current NEMA NU 2-2018 standard does not account for count rate performance gains due to TOF in the NECR evaluation. The relationship between image SNR and total-body NECR in long axial FOV PET was assessed for the first time using the uEXPLORER total-body PET/CT scanner.

Ultrafast 30-s total-body PET/CT scan: a preliminary study

PURPOSE

The aim of this study is to explore the diagnostic value of the images obtained in ultrafast 30-s acquisition time by the total-body PET/CT (¹⁸F-FDG injection dose of about 3.7 MBq/kg), and to evaluate whether they can meet the requirements of clinical diagnosis or not.

METHODS

This retrospective study explored the clinical value of ultrafast 30-s ¹⁸F-FDG total-body PET/CT in 88 oncology patients, using the post-surgical pathological diagnosis as the reference standard. The data were acquired over 300 s and reconstructed using all 300-s data (G300) and only the initial 30 s (G30). Two readers independently assessed all images qualitatively and quantitatively. The diagnostic performance was compared between G300 and G30.

RESULTS

The G300 average qualitative score was higher than G30 (P < 0.001). G300 and G30 also differed quantitatively in the liver and mediastinum SUV_max, SD, and SNR (all P < 0.001), but had similar sensitivities (89.09% vs. 86.36%, P = 0.250). The G300 group had higher accuracy (79.73%) and a larger area under the curve (0.709) than G30 (77.70% and 0.695, respectively; all P > 0.05).

CONCLUSION

The 30-s total-body PET/CT could meet clinical diagnostic requirements for malignant tumors in patients intolerant to prolonged horizontal positioning.

Diagnostic performance of total-body 18F-FDG PET/CT with fast 2-min acquisition for liver tumours: comparison with conventional PET/CT

PURPOSE

To comparatively evaluate the diagnostic performances of total-body ¹⁸F-fluorodeoxyglucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT) with fast 2-min acquisition and conventional PET/CT in liver cancer patients.

METHODS

This study included 156 patients with liver tumours. Seventy-eight patients underwent total-body PET/CT. PET raw data were reconstructed using acquisition durations of 2 min (G2) and 15 min (G15). Another 78 patients with liver lesions (control patients) underwent conventional uMI780 PET/CT (G780). All patients were evaluated based on TNM staging. The maximum tumour standardized uptake value (tumour SUVmax), mean normal liver SUV (SUVmean), and tumour SUVmax-to-liver SUVmean ratio (TLR) were determined for all patients. G15 data were used as the reference in the lesion detectability analysis. The diagnostic performances of PET/CT in terms of visual parameters and of PET in terms of semi-quantitative parameters such as SUVmax and TLR were evaluated. Receiver operating characteristics (ROC) curve analysis of SUVmax and TLR at G2 was performed. Pathologic findings of surgical specimens served as the gold standard for all patients.

RESULTS

The lesions found in G15 were also noted in G2; three lymph nodes were missed in G2. However, no significant difference was found in the TNM stage among G2, G15, and G780. For benign and malignant lesions, the liver SUVmean in G2 and G15 was higher than that in G780 (all P < 0.05). The tumour SUVmax and TLR in G2 were equivalent to those in G15 and G780 regardless of whether the lesions were benign or malignant. ROC curve analysis (SUVmax cutoff: 4.34, TLR cutoff: 1.34) demonstrated that G2 also had good sensitivity in detecting liver cancer.

CONCLUSION

The diagnostic performance of total-body PET/CT in G2 was comparable to that in G15 among liver cancer patients. Further, the diagnostic efficiency of total-body PET/CT imaging with fast 2-min acquisition and conventional PET/CT was similar.

Exploration of the total-body PET/CT reconstruction protocol with ultra-low 18F-FDG activity over a wide range of patient body mass indices

Purpose

The purpose of this study was to investigate the image quality and diagnostic performance of different reconstructions over a wide range of patient body mass indices (BMIs) obtained by total-body PET/CT with ultra-low ¹⁸F-FDG activity (0.37 MBq/kg).

Methods

A total of 63 patients who underwent total-body PET/CT with ultra-low activity (0.37 MBq/kg) ¹⁸F-FDG were enrolled. Patients were grouped by their BMIs. Images were reconstructed with the following two algorithms: the ordered subset expectation maximization (OSEM) algorithm (2, 3 iterations), both with time of flight (TOF) and point spread function (PSF) corrections (hereinafter referred as OSEM2, OSEM3) and HYPER Iterative algorithm (β-values of 0.3, 0.4, 0.5, 0.6) embedded TOF and PSF technologies (hereinafter referred as HYPER0.3, HYPER0.4, HYPER0.5 and HYPER0.6, respectively). Subjective image quality was assessed by two experienced nuclear medicine physicians according to the Likert quintile, including overall image quality, image noise and lesion conspicuity. The standard deviation (SD) and signal-to-noise ratio (SNR) of the liver, and maximum standard uptake value (SUV_max), peak standard uptake value (SUV_peak), tumour background ratio (T/N) and the largest diameter of lesions were quantitatively analysed by a third reader who did not participate in the subjective image assessment.

Results

Increased noise was associated with increased BMI in all reconstruction groups. Significant differences occurred in the liver SNR among BMI categories of OSEM reconstructions (P < 0.001) but no difference was seen in the HYPER Iterative reconstructions between any of the BMI categories (P > 0.05). With the increase in BMI, overall image quality and image noise scores decreased significantly in all reconstructions, but there was no statistically significant difference of lesion conspicuity. The overall image quality score of the obese group was not qualified (score = 2.7) in OSEM3, while the others were qualified. The lesion conspicuity scores were significantly higher in HYPER Iterative reconstructions and lower in OSEM2 than in OSEM3 (all P < 0.05). The values of SUV_max, SUV_peak and T/N in HYPER0.3, HYPER0.4 and HYPER0.5 were higher than those in OSEM3. In different reconstructions, there was a correlation between lesion size (median, 1.55 cm; range, 0.7–11.0 cm) and SUV_peak variation rate compared to OSEM3 (r = 0.388, − 0.515, − 0.495, − 0.464, and − 0.423, respectively, and all P < 0.001).

Conclusion

Considering the image quality and lesion analysis in ¹⁸F-FDG total-body PET/CT with ultra-low activity injection, OSEM reconstructions with 3 iterations meet the clinical requirements in patients with BMI < 30. In patients with BMI ≥ 30, it is recommended that the HYPER Iterative algorithm (β-value of 0.3–0.5) be used to ensure consistent visual image quality and quantitative assessment.

Increased uptake of 68Ga-DOTA-FAPI-04 in bones and joints: metastases and beyond

PURPOSE

To describe the uptake of ⁶⁸Gallium-labelled fibroblast activation protein inhibitor (⁶⁸Ga-FAPI) in the bones and joints for better understanding of the role of ⁶⁸Ga-FAPI PET in benign and malignant bone lesions and joint diseases.

METHODS

All 129 ⁶⁸Ga-FAPI PET/MR or PET/CT scans from June 1, 2020, to February 20, 2021, performed at our PET center were retrospectively reviewed. Foci of elevated ⁶⁸Ga-FAPI uptake in the bones and joints were identified. All lesions were divided into malignant and benign diseases. Benign lesions included osteofibrous dysplasia, periodontitis, degenerative bone diseases, arthritis, and other inflammatory or trauma-related abnormalities. The number, locations, and SUVmax of all lesions were recorded and analyzed. The detectability of ⁶⁸Ga-FAPI PET and ¹⁸F-FDG PET in patients who had two scans was also compared.

RESULTS

Elevated uptake of ⁶⁸Ga-FAPI in/around the bones and joints was found in 82 cases (63.57%). A total of 295 lesions were identified, including 94 (31.9%) malignant lesions (all were metastases) and 201 (68.1%) benign lesions. The benign lesions consisted of 13 osteofibrous dysplasia, 48 degenerative bone disease, 33 periodontitis, 56 arthritis, and 51 other inflammatory or trauma-related abnormalities. The spine, shoulder joint, alveolar ridge, and pelvis were the most commonly involved locations. Bone metastases were mainly distributed in the spine, pelvis, and ribs. Among benign diseases, periodontitis and arthritis are site-specific. The mean SUVmax of bone metastases was significantly higher than that of benign diseases (7.14 ± 4.33 vs. 3.57 ± 1.60, p < 0.001), but overlap existed. The differences in SUVmax among subgroups of benign diseases were statistically significant (p < 0.001), with much higher uptake in periodontitis (4.45 ± 1.17). ⁶⁸Ga-FAPI PET identified much more lesions than ¹⁸F-FDG PET (104 vs. 48) with higher uptake value.

CONCLUSION

⁶⁸Ga-FAPI accumulated in both bone metastases and some benign diseases of the bones and joints. Although the uptake of ⁶⁸Ga-FAPI was often higher in bone metastases, this finding cannot be used to distinguish between benign and malignant lesions. ⁶⁸Ga-FAPI PET also has the potential to locate and evaluate the extent of both malignant tumor and benign diseases in bones and joints.

TRIAL REGISTRATION

NCT04554719, NCT04605939. Registered September 8, 2020 and October 25, 2020-retrospectively registered, http://clinicaltrails.gov/show/NCT04554719 ; http://clinicaltrails.gov/show/NCT04605939.