Positron Range Corrections and Denoising Techniques for Gallium-68 PET Imaging: A Literature Review

Advancements in the development of radiopharmaceuticals for nuclear medicine applications in the treatment of bone metastases

Bone metastases are a painful and complex condition that overwhelmingly impacts the prognosis and quality of life of cancer patients. Over the years, nuclear medicine has made remarkable progress in the diagnosis and management of bone metastases. This review aims to provide a comprehensive overview of the recent advancements in nuclear medicine for the diagnosis and management of bone metastases. Furthermore, the review explores the role of targeted radiopharmaceuticals in nuclear medicine for bone metastases, focusing on radiolabeled molecules that are designed to selectively target biomarkers associated with bone metastases, including osteocytes, osteoblasts, and metastatic cells. The applications of radionuclide-based therapies, such as strontium-89 (Sr-89) and radium-223 (Ra-223), are also discussed. This review also highlights the potential of theranostic approaches for bone metastases, enabling personalized treatment strategies based on individual patient characteristics. Importantly, the clinical applications and outcomes of nuclear medicine in osseous metastatic disease are discussed. This includes the assessment of treatment response, predictive and prognostic value of imaging biomarkers, and the impact of nuclear medicine on patient management and outcomes. The review identifies current challenges and future perspectives on the role of nuclear medicine in treating bone metastases. It addresses limitations in imaging resolution, radiotracer availability, radiation safety, and the need for standardized protocols. The review concludes by emphasizing the need for further research and advancements in imaging technology, radiopharmaceutical development, and integration of nuclear medicine with other treatment modalities. In summary, advancements in nuclear medicine have significantly improved the diagnosis and management of osseous metastatic disease and future developements in the integration of innovative imaging modalities, targeted radiopharmaceuticals, radionuclide production, theranostic approaches, and advanced image analysis techniques hold great promise in improving patient outcomes and enhancing personalized care for individuals with bone metastases.

Image Denoising of Low-Dose PET Mouse Scans with Deep Learning: Validation Study for Preclinical Imaging Applicability

PURPOSE

Positron emission tomography (PET) image quality can be improved by higher injected activity and/or longer acquisition time, but both may often not be practical in preclinical imaging. Common preclinical radioactive doses (10 MBq) have been shown to cause deterministic changes in biological pathways. Reducing the injected tracer activity and/or shortening the scan time inevitably results in low-count acquisitions which poses a challenge because of the inherent noise introduction. We present an image-based deep learning (DL) framework for denoising lower count micro-PET images.

PROCEDURES

For 36 mice, a 15-min [18F]FDG (8.15 ± 1.34 MBq) PET scan was acquired at 40 min post-injection on the Molecubes β-CUBE (in list mode). The 15-min acquisition (high-count) was parsed into smaller time fractions of 7.50, 3.75, 1.50, and 0.75 min to emulate images reconstructed at 50, 25, 10, and 5% of the full counts, respectively. A 2D U-Net was trained with mean-squared-error loss on 28 high-low count image pairs.

RESULTS

The DL algorithms were visually and quantitatively compared to spatial and edge-preserving denoising filters; the DL-based methods effectively removed image noise and recovered image details much better while keeping quantitative (SUV) accuracy. The largest improvement in image quality was seen in the images reconstructed with 10 and 5% of the counts (equivalent to sub-1 MBq or sub-1 min mouse imaging). The DL-based denoising framework was also successfully applied on the NEMA-NU4 phantom and different tracer studies ([18F]PSMA, [18F]FAPI, and [68 Ga]FAPI).

CONCLUSION

Visual and quantitative results support the superior performance and robustness in image denoising of the implemented DL models for low statistics micro-PET. This offers much more flexibility in optimizing preclinical, longitudinal imaging protocols with reduced tracer doses or shorter durations.

Biodistribution and radiation dosimetry of multiple tracers on total-body positron emission tomography/computed tomography

Background

[18F]F-FDG, [68Ga]Ga-PSMA-11, and [68Ga]Ga-FAPI-04 have achieved good results in multiple clinical trials and clinical practice, but the imaging of these tracers is limited to traditional short-axis positron emission tomography/computed tomography (PET/CT). Therefore, we aimed to use total-body PET/CT dynamic scanning to describe whole-body biodistribution of these three tracers and to calculate more precise radiation doses.

Methods

Total-body PET/CT (uExplorer, United Imaging Healthcare) dynamic scanning was performed on 54 patients, including 30 patients with [18F]F-FDG, 10 patients with [68Ga]Ga-PSMA-11, and 14 patients with [68Ga]Ga-FAPI-04. A 60-minute dynamic scanning of whole body was performed simultaneously after bedside bolus injection of the corresponding tracers. The dynamic sequence of 92 frames was quantitatively analyzed by the Pmod4.0 software. Whole body biodistribution was calculated as time-activity curves (TACs) describing dynamic uptake patterns in the subject's major organs, followed by calculation of tracer kinetics and cumulative organ activity. Finally, combined with the OLINDA/EXM software, effective doses of the different tracers and individual organ doses were calculated.

Results

In a systematic TAC analysis of three tracers, we identified distinct biodistribution patterns in major organs. [68Ga]Ga-PSMA-11 showed a trend of rapid increasing and slow decreasing in liver, spleen, muscle, and bone. In the heart, stomach, brain, and lung, tracer decreased rapidly after rapid increasing. Similarly, tracer uptake in the kidney and urinary bladder increased gradually. [68Ga]Ga-FAPI-04 showed a rapid increasing and rapid decreasing trend in brain, lung, liver, spleen, bone, heart, kidney, and stomach. The mean effective dose of [68Ga]Ga-PSMA-11 was 1.47E-02 mSv/MBq, and the mean effective doses of [18F]F-FDG and [68Ga]Ga-FAPI-04 were comparable (2.52E-02 mSv/MBq and 2.23E-02 mSv/MBq). The mean effective dose of [18F]F-FDG was lower than that reported in the literature measured by previous short-axis PET, while both [68Ga]Ga-PSMA-11 and [68Ga]Ga-FAPI-04 had higher value than previously reported value.

Conclusions

[18F]F-FDG, [68Ga]Ga-PSMA-11 and [68Ga]Ga-FAPI-04 have good biodistribution in human organs. Real-time high-sensitivity dynamic scanning with total-body PET/CT is a very effective way to accurately calculate biodistribution and effective dose of positron-labeled radiopharmaceuticals.

Artificial intelligence-based 68Ga-DOTATOC PET denoising for optimizing 68Ge/68Ga generator use throughout its lifetime

Introduction

The yield per elution of a 68Ge/68Ga generator decreases during its lifespan. This affects the number of patients injected per elution or the injected dose per patient, thereby negatively affecting the cost of examinations and the quality of PET images due to increased image noise. We aimed to investigate whether AI-based PET denoising can offset this decrease in image quality parameters.

Methods

All patients addressed to our PET unit for a 68Ga-DOTATOC PET/CT from April 2020 to February 2021 were enrolled. Forty-four patients underwent their PET scans according to Protocol_FixedDose (150 MBq) and 32 according to Protocol_WeightDose (1.5 MBq/kg). Protocol_WeightDose examinations were processed using the Subtle PET software (Protocol_WeightDoseAI). Liver and vascular SUV mean were recorded as well as SUVmax, SUVmean and metabolic tumour volume (MTV) of the most intense tumoural lesion and its background SUVmean. Liver and vascular coefficients of variation (CV), tumour-to-background and tumour-to-liver ratios were calculated.

Results

The mean injected dose of 2.1 (0.4) MBq/kg per patient was significantly higher in the Protocol_FixedDose group as compared to 1.5 (0.1) MBq/kg for the Protocol_WeightDose group. Protocol_WeightDose led to noisier images than Protocol_FixedDose with higher CVs for liver (15.57% ± 4.32 vs. 13.04% ± 3.51, p = 0.018) and blood-pool (28.67% ± 8.65 vs. 22.25% ± 10.37, p = 0.0003). Protocol_WeightDoseAI led to less noisy images than Protocol_WeightDose with lower liver CVs (11.42% ± 3.05 vs. 15.57% ± 4.32, p < 0.0001) and vascular CVs (16.62% ± 6.40 vs. 28.67% ± 8.65, p < 0.0001). Tumour-to-background and tumour-to-liver ratios were lower for protocol_WeightDoseAI: 6.78 ± 3.49 vs. 7.57 ± 4.73 (p = 0.01) and 5.96 ± 5.43 vs. 6.77 ± 6.19 (p < 0.0001), respectively. MTVs were higher after denoising whereas tumour SUVmax were lower: the mean% differences in MTV and SUVmax were + 11.14% (95% CI = 4.84–17.43) and −3.92% (95% CI = −6.25 to −1.59).

Conclusion

The degradation of PET image quality due to a reduction in injected dose at the end of the 68Ge/68Ga generator lifespan can be effectively counterbalanced by using AI-based PET denoising.